Rewrote % of the original text.

How Does Machine Learning Work


#complex machine     #machine algorithms     #human capabilities     #machine theory     #machine systems     #computer systems     #machine technology     #deep learning     #machine learning     #training data    

Machine learning is a set of programming tools for working with data, and deep learning or amplification is a subset of machine learning. 33 Automatic learning is a set of programming tools for data processing, and deep learning or amplification is a subset of machine learning. 33 Automatic learning is a set of programming tools for working with data, and in - depth or amplification is a subset of the software. 33 In general, if you want to develop your artificial intelligence career, you can start with a background in software development and take the theory of machine learning, or you can start with the theory of machine learning and communication, and then gradually increase the programming skills to work in machine learning. 33 In general, if you want to advance your artificial intelligence career, you can start with a background in software development and take the theory of automatic learning, or you can start with the theory of machine science and communication and gradually learn the programming skills to work in automatic learning. 33 In general, if you want to advance your artificial intelligence career, you can start with a background in the development of software and take up the theory of automatic learning, or you can start with the theory of automatic communication and communication, and then gradually increase the cuttings of programming to learn machines. 33 In general, if you want to advance your artificial intelligence career, you can start with a background in the development of software and take up the theory of machine science, or you can start with the theory of automatic learning and communication, and gradually increase the programming cutbacks to learn machines. 33 In practice, machine learning engineers rely more on their software engineering cutlets, while data scientists are more dependent on their knowledge of the theory of machine science and statistical inference, as well as on the ability to communicate such data insights. 33 In practice, machine learning engineers rely more on their software engineering cutlets, while data scientists are more dependent on their knowledge of the theory of machine science and statistical inference, as well as on the ability to communicate such observations. 33 In practice, automatic learning engineers will be more inclined to use their software engineering cutlets, while data scientists are more dependent on their knowledge of the theory of machine science and statistical inference, as well as on the ability to communicate such observations. 33 In practice, automatic learning engineers rely more on their software engineering cutlets, while data scientists are more dependent on their knowledge of the theory of automatic learning and statistical inference, as well as on the ability to communicate such observations. 33 You will start working with critical data science tools such as Pandas and science kits, and you will gain a real sense of how to implement the theory of machine learning. 33 You will work with critical data science tools such as Pandas and science kits, and you will gain a real sense of how to implement the theory of machine learning. 33 You will begin to work with critical it tools, such as Pandas and science kits, and you will gain a real sense of how to implement the theory of automatic learning. 33

Machine learning is more than just a buzzword - it's a technology tool that works on the concept that a computer can learn information without human mediation. 26 Automatic learning is more than just a buzzword - it's a technology tool that works on the concept that a computer can learn information without human mediation. 26 Automatic learning is more than a buzzword - it is a technology tool that works according to the concept that a computer can learn information without human mediation. 26 Automatic learning is more than a buzzword - it's a technology tool that works on the concept that a computer could learn information without human mediation. 26 Automatic learning is more than a buzzword - it's a technology tool that works according to the concept that a computer could learn information without human mediation. 26 With traditional machine learning, the computer learns how to decipher information as it has been labelled by humans - hence machine learning is a program that teaches from a model of data sets with human tags. 26 Thanks to traditional machine learning, the computer learns how to decipher information as it is labelled by people - so machine learning is a program that teaches people from a model of data sets with human tags. 26 Thanks to traditional machine learning, the computer teaches the computer how to decipher information in the way it was labelled by people - so machine learning is a program learned from a model of data sets with human tags. 26 With traditional automatic learning, the computer teaches the computer how to decipher information in the way it was labelled by man - hence automatic learning is a program that teaches from a model of data sets with human tags. 26 Thanks to traditional automatic learning, the computer teaches the computer how to decipher information as it is labelled by people, which means that automatic learning is a programme learned from the data sets with a human label. 26 In machine learning without supervision, the machine is able to understand and deduce patterns from data without human intervention. 26 In the case of unattended machine learning, the machine is capable of understanding and deducting data models without human intervention. 26 In machine learning without supervision, the machine is capable of understanding and deducting data patterns without human intervention. 26 In the case of unattended learning machines, the machine is capable of understanding and deducting data models without human intervention. 26

Machine learning is a data analysis technique that teaches computers to do what is natural for humans and animals : learn from experience. Automatic learning is a data analysis technique that teaches computers to do what is natural for humans and animals : learn from experience. Automatic learning is a computer - aided analysis technique that teaches computer science to do what is natural for people and animals : learn from experience. Automatic learning is a computer - aided analysis technique to do what is natural for people and animals : learn from experience. Automatic learning is a data analysis technique that teaches computer science to do what is natural for people and animals : learning from experience. Machine learning algorithms use computational methods to "learn" information directly from data without relying on a predetermined equation as a model. Algorithms for automatic learning use computerized methods to "learn" information directly from data without relying on a predetermined equation as a model. Algorithms for automatic learning use computerized methods to "learn" directly from data, without relying on a pre - defined equation as a model. Algorithms for automatic learning use computer science to "learn" information directly from data, without having to rely on a pre - defined equation as a model. Machine learning algorithms find natural patterns in data that generate insight and help you make better decisions and forecasts. Automatic learning algorithms find natural patterns in data that provide insight and help you make better decisions and forecasts. Automatic learning algorithms find natural patterns in data that provide insight and support in making better decisions and forecasts. Automatic learning algorithms find natural models in data that provide insight and support in making better decisions and forecasts. Matlab is an ideal environment to apply machine learning to your data analysis with the tools and functions you need to manage large amounts of data, as well as applications to enable automatic learning. Matlab is an ideal setting for the application of machine learning to data analysis with tools and features to manage large amounts of data, as well as applications to enable automatic learning in data analysis. With the tools and features to manage large amounts of data, as well as applications to provide access to automatic learning, MATLAB is an ideal setting for the application of machine science to your data analysis. Matlab is an ideal setting for the application of machine science to your data analysis with tools and features to help you manage large amounts of data and applications. Matlab is an ideal setting for the application of machine science to your data analysis with the help of tools and features to manage large amounts of data and applications to enable automatic learning. Integrate machine learning models into enterprise systems, clusters and clouds, and target models with embedded real - time hardware. Integrate machine learning patterns into enterprise systems, clusters and clouds, and target models with embedded real - time hardware. Integrate machine learning patterns into enterprise, cluster and cloud systems and target models with embedded real - time hardware. Integrate automatic learning patterns into enterprise, cluster and cloud systems and target models with embedded real - time hardware.

Machine learning is simply a general term for defining different algorithms of learning that generate quasi - learning from examples ( unlabelled or labelled ). 32 Machine learning is simply a general term for defining different algorithms of learning that generate quasi - learning from ( unlabelled or labelled ) examples. 32 Automatic learning is simply a general term for defining different algorithms of learning that generate quasi - learning from ( unchecked ) examples. 32 Automatic learning is simply a general term for defining different algorithms of learning that generate quasi - learning from ( unlabelled or labelled ) examples. 32 Automatic learning is simply a general term for defining different algorithms of science that quasi - learn from ( unlabelled or labelled ) examples. 32 Machine learning is the study of algorithms of algorithms capable of classifying information they have never seen before by learning patterns of learning similar information. 32 Automatic learning is the study of algorithms of algorithms capable of classifying information that they have not seen before by learning patterns from similar information. 32 Automatic learning is the study of algorithms of algorithms capable of classifying information that they have never seen before by learning patterns of similar information. 32 Automatic learning is the study of algorithms of algorithms capable of classifying information that they have never seen before, by learning patterns of learning similar information. 32 Automatic learning is the study of algorithms of algorithms capable of classifying information that they have never seen before, through patterns of learning to learn similar information. 32 Wikipedia : automatic learning is a scientific discipline that deals with the design and development of algorithms in order to enable computers to develop behaviours based on empirical data, such as sensor or database data. 32 Wikipedia : automatic learning is a scientific discipline that deals with designing and developing algorithms to enable computers to develop behaviour based on empirical data, such as sensor or database data. 32

Just as there are almost unlimited machine learning applications, there is no lack of automatic learning algorithms. 23 Just as there are almost unlimited machine learning applications, there is no lack of algorithms for automatic learning. 23 Just as there are almost unlimited possibilities of automatic learning, there is no lack of algorithms to learn machines. 23 As automatic learning becomes increasingly important for business operations and AI is becoming more and more useful in business environments, the wars on the machine learning platform will only intensify. 23 As automatic learning becomes increasingly important for business operations and artificial intelligence becomes more practical in business environments, the wars on the machine learning platform will only intensify. 23 As automatic learning becomes increasingly important for businesses and AI is becoming more and more useful in business environments, the wars on the machine learning platform will only intensify. 23 In today's world, every successful system has an automatic Learning algorithm at its core. 23 In today's world, all good systems have an automatic Learning algorithm at their core. 23 In the current world, every successful system has an automatic Learning algorithm at its core. 23 The processes involved in automatic learning are comparable to those of data mining and predictive modelling. 23

Different processes, techniques and methods can be applied to one or more types of algorithms for automatic learning to improve their performance. 8 Different processes, techniques and methods may apply to one or more types of algorithms for automatic learning to improve their performance. 8 Function - learning algorithms, also known as representational algorithms, often try to preserve information in their inputs, but also to transform it in a useful way, often as a pre - processing phase before classification or forecasting. 8 Function - based algorithms, also known as representational algorithms, often try to preserve information in their inputs, but also to transform it in a useful way, often as a pre - processing phase before classification or forecasting. 8 Function - based algorithms, also known as presentation - based algorithms, often try to keep information in their inputs, but also to transform it in a useful way, often as a pre - process phase before classification or forecasting. 8 Function - based algorithms, also known as presentation - based algorithms, often try to keep the information in their inputs, but also to transform it in a useful way, many times as a pre - process phase before classification or forecasting. 8 Functional learning is motivated by the fact that automatic learning tasks such as classification often require mathematical and computationally useful input. 8 Rule - based machine learning is a general term for any method of machine learning that identifies, teaches or develops "rules" for storing, manipulating or applying knowledge. 8 Rule - based machine learning is a generic term for any method of machine learning that identifies, teaches or develops "rules" for storing, manipulating or applying knowledge. 8 Automatic learning is a generic term for every method of machine learning that identifies, teaches or develops "rules" for storing, manipulating or applying knowledge. 8 Automatic learning is a generic term for every method of machine science that identifies, teaches or develops "rules" for storing, manipulating or applying knowledge. 8 Although automatic learning has been transforming in some areas, automatic learning programmes often do not produce the desired results. 8

Machine learning can be used to achieve higher levels of efficiency, especially when used on the Internet of Things. 5 Automatic learning can be used to achieve higher levels of efficiency, especially when used on the Internet of Things. 5 Automatic learning can be used to achieve greater efficiency, especially when used on the Internet of Things. 5 Automatic learning can be used to increase efficiency, especially when used on the Internet of Things. 5 Machine learning is based on the ability to use computers to probe data for structures, although we do not have a theory of how the structure looks. 5 Automatic learning has been developed on the basis of computer - assisted ability to probe data for structures, although we do not have a theory of how the structure looks. 5 Automatic learning has been developed on the basis of computer - assisted ability to detect data for structures, although we do not have a theory of how the structure looks. 5 Automatic learning has been developed on the basis of computer - assisted ability to detect data for structures, although we do not have a theory of how the structure is. 5 Because machine learning often takes an iterative approach to data learning, learning can be easily automated. 5 Because machine learning often takes an iterative approach to data acquisition, learning can be easily automated. 5 Since automatic learning often takes an iterative approach to data acquisition, it is easy to automate learning. 5 In - depth learning combines the advances in computing power and special types of neural networks to learn complex patterns in large amounts of data. 5 In - depth learning combines the advances in computing power and specific types of neural networks to learn complex patterns in large amounts of data. 5 In - depth learning combines the advances in computing power and specific types of neural networks to learn complex patterns across large amounts of data. 5 In - depth learning combines the advances in computational power and specific types of neuronal networks to learn complex patterns in vast amounts of data. 5 In - depth learning combines the advances in computational power and specific types of neuronal networks to learn complex data patterns. 5 Sas's graphical user interfaces help to create machine learning models and implement iterative machine learning. 5 Sas's graphical user interfaces allow you to create machine learning models and implement iterative machine learning. 5 Sas's graphical user interfaces allow you to create machine learning patterns and implement iterative machine learning. 5 From drilling holes to the prevention of health care fraud, discover some of SAS's new technologies with IoT technologies and machine learning. 5 From drilling holes to the prevention of healthcare fraud, discover some of SAS's new technologies with IoT technologies and machine learning. 5 From drilling holes to the prevention of healthcare fraud, discover some of SAS's new technologies with IoT technology and machine science. 5

Deep learning, machine learning and artificial intelligence can be seen as a group of Russian dolls, which start with the smallest ones and work. 11 Deep learning, automatic learning and artificial intelligence can be seen as a group of Russian dolls, which start with the smallest ones and work. 11 Deep learning is a subset of machine learning, and machine learning is a subset of AI, which is an umbrella term for any computer program that does something intelligent. 11 Deep learning is a subset of machine learning, and automatic learning is a subset of AI, which is an umbrella term for any computer program that does something intelligent. 11 Deep learning is a subset of machine learning, and automatic learning is a subset of AI, which is an umbrella term for any computer software that does something intelligent. 11 Deep learning is a subset of machine science, and automatic learning is a subset of AI, which is an umbrella name for any computer program that does something intelligent. 11 Deep learning is a sub - group of machine learning, and AI is a subset of AI, which is an umbrella name for any computer software that does something intelligent. 11 Deep learning is a sub - group of machine science, and AI is a subset of AI, which is an umbrella name for any computer software that does something intelligent. 11 For example, symbolic logic - rule engines, expert systems and knowledge charts - could all be described as AI, and none of them are machine learning. 11 For example, symbolic logic - rule engines, systems of expertise and knowledge charts - can all be described as AI, and none of them are machine learning. 11 For example, symbolic logic - rule engines, systems of expertise and knowledge charts - can all be described as AI, and none of them are machine science. 11 For example, symbolic logic - rule engines, systems of expertise and knowledge charts - can all be called AI, and none of them are machine science. 11 In 1959, Arthur Samuel, one of the pioneers of automatic learning, described automatic learning as a "study area that enables computers to learn without explicitly programming ". 11 In 1959, artur Samuel, one of the pioneers of automatic learning, defined automatic learning as a "study area that allows computer science to be learned without explicitly programming. 11

Machine learning allows computers to take on tasks that have so far been done only by people. 15 Automatic learning allows computers to take on tasks that have so far been done only by people. 15



How Does Machine Learning Work

#complex machine     #machine algorithms     #human capabilities     #machine theory     #machine systems     #computer systems     #machine technology     #deep learning     #machine learning     #training data    

"Machine learning is a set of programming tools to work with data and deep learning or reinforcement learning is a subset within that . " 33 "Broadly speaking , if you want to develop your career in artificial intelligence , you can get started with a software development background and pick up the machine learning theory , or you can start off with the machine learning theory and communication skills and gradually pick up the programming chops to work in machine learning . " 33 "In practice , machine learning engineers will lean more on their software engineering chops , while data scientists rely more on their knowledge of machine learning theory and statistical inference , along with the ability to communicate those data insights . " 33 "You 'll start working with critical data science tools , such as Pandas and sci - kit learn , and get a real feel for how to put machine learning theory into practice . " 33

"Machine learning is more than just a buzz - word -- it is a technological tool that operates on the concept that a computer can learn information without human mediation . " 26 "With traditional machine learning , the computer learns how to decipher information as it has been labeled by humans -- hence , machine learning is a program that learns from a model of human - labeled datasets . " 26 "In unsupervised machine learning , the machine is able to understand and deduce patterns from data without human intervention . " 26

"Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals : learn from experience . " 0 "Machine learning algorithms use computational methods to " learn " information directly from data without relying on a predetermined equation as a model . " 0 "Machine learning algorithms find natural patterns in data that generate insight and help you make better decisions and predictions . " 0 "With tools and functions for handling big data , as well as apps to make machine learning accessible , MATLAB is an ideal environment for applying machine learning to your data analytics . " 0 "Integrate machine learning models into enterprise systems , clusters , and clouds , and target models to real - time embedded hardware . " 0

"Machine learning is simply a generic term to define a variety of learning algorithms that produce a quasi learning from examples ( unlabeled / labeled ) . " 32 "Machine learning is the study in computing science of making algorithms that are able to classify information they have n't seen before , by learning patterns from training on similar information . " 32 "Shamelessly ripped from Wikipedia : Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data , such as from sensor data or databases . " 32 "Basically , machine learning is a very wide - open discipline that contains many methods and algorithms that make it impossible for there to be 1 answer to your 3rd question . " 32

"Just as there are nearly limitless uses of machine learning , there is no shortage of machine learning algorithms . " 23 "As machine learning continues to increase in importance to business operations and AI becomes ever more practical in enterprise settings , the machine learning platform wars will only intensify . " 23 "In today 's world , every system that does well has a machine Learning algorithm at its heart . " 23 "Processes involved in machine learning are similar to that of data mining and predictive modeling . " 23

"Various processes , techniques and methods can be applied to one or more types of machine learning algorithms to enhance their performance . " 8 "Feature learning algorithms , also called representation learning algorithms , often attempt to preserve the information in their input but also transform it in a way that makes it useful , often as a pre - processing step before performing classification or predictions . " 8 "Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process . " 8 "Rule - based machine learning is a general term for any machine learning method that identifies , learns , or evolves " rules " to store , manipulate or apply knowledge . " 8 "Although machine learning has been transformative in some fields , machine - learning programs often fail to deliver expected results . " 8

"Machine learning can be used to achieve higher levels of efficiency , particularly when applied to the Internet of Things . " 5 "Machine learning has developed based on the ability to use computers to probe the data for structure , even if we do not have a theory of what that structure looks like . " 5 "Because machine learning often uses an iterative approach to learn from data , the learning can be easily automated . " 5 "Deep learning combines advances in computing power and special types of neural networks to learn complicated patterns in large amounts of data . " 5 "SAS graphical user interfaces help you build machine learning models and implement an iterative machine learning process . " 5 "From drilling holes to preventing health care fraud , learn about some of the new technologies SAS has patented with IoT and machine learning technologies . " 5

"You can think of deep learning , machine learning and artificial intelligence as a set of Russian dolls nested within each other , beginning with the smallest and working out . " 11 "Deep learning is a subset of machine learning , and machine learning is a subset of AI , which is an umbrella term for any computer program that does something smart . " 11 "For example , symbolic logic - rules engines , expert systems and knowledge graphs - could all be described as AI , and none of them are machine learning . " 11 "In 1959 , Arthur Samuel , one of the pioneers of machine learning , defined machine learning as a " field of study that gives computers the ability to learn without being explicitly programmed . " 11

"Machine learning is enabling computers to tackle tasks that have , until now , only been carried out by people . " 15 "Machine learning may have enjoyed enormous success of late , but it is just one method for achieving artificial intelligence . " 15 "Alongside machine learning , there are various other approaches used to build AI systems , including evolutionary computation , where algorithms undergo random mutations and combinations between generations in an attempt to " evolve " optimal solutions , and expert systems , where computers are programmed with rules that allow them to mimic the behavior of a human expert in a specific domain , for example an autopilot system flying a plane . " 15 "However , Facebook 's approach of using publicly available data to train systems could provide an alternative way of training systems using billion - strong datasets without the overhead of manual labeling . " 15 "Were semi - supervised learning to become as effective as supervised learning , then access to huge amounts of computing power may end up being more important for successfully training machine - learning systems than access to large , labelled datasets . " 15

"Machine learning technology teaches computers how to perform tasks by learning from data a instead of being explicitly programmed . " 27 "Determine if machine learning technology is right for your company , and get practical guidance on how to build a smart AI strategy . " 27 "Machine learning can analyze big , complex , and streaming data , and find insights a including predictive insights a that are beyond human capabilities . " 27 "Manufacturers collect a huge amount of data from plant sensors and the Internet of Things a which is perfect for machine learning . " 27

"This is due in part to amazing developments in machine learning , deep learning , and neural networks . " 16 "As you have most likely already gathered , machine learning is the branch of AI dedicated to endowing machines with the ability to learn . " 16 "Currently , machine learning applications allow for a machine to train in a certain task by analyzing examples of that task . " 16

"Use machine learning to build stronger underwriting models based on a wide variety of data points . " 22 "Reinforcement learning is the most abstract approach and based entirely on the machine , often referred to as the " learning agent " , learning through trial and error . " 22 "Through exploration and exploitation of its environment , the learning agent , fueled by advanced machine learning algorithms , ultimately gains enough knowledge to begin to demonstrate almost human - like levels of artificial intelligence . " 22 "Supervised and reinforcement learning are incredible tools that can be applied to gain insights and do more with unstructured data than ever before . " 22 "One reason is that for most machine learning models , you are trying to get a computer to make sense of a data - set with an incredible amount of variation . " 22

"Machine Learning ( ML ) is coming into its own , with a growing recognition that ML can play a key role in a wide range of critical applications , such as data mining , natural language processing , image recognition , and expert systems . " 19 "Neural networks are well suited to machine learning models where the number of inputs is gigantic . " 19 "Deep learning is a machine learning method that relies on artificial neural networks , allowing computer systems to learn by example . " 19

"Off late , though , " Machine Learning " and " Deep Learning " have surfaced , with many asking what exactly each of these are . " 37 "Machine Learning , at its most basic form , is the practice of using algorithms to parse data , learn from it , and then make a determination or prediction about something in the world . " 37 "Machine Learning , at its core , is really just making a line of best fit , except in many dimensions . " 37 "Latest News , Info and Tutorials on Artificial Intelligence , Machine Learning , Deep Learning , Big Data and what it means for Humanity . " 37

"Well , Machine Learning is a concept which allows the machine to learn from examples and experience , and that too without being explicitly programmed . " 20 "Machine Learning is a subset of artificial intelligence which focuses mainly on machine learning from their experience and making predictions based on its experience . " 20 "If you wanna learn about machine learning in depth , then stay tuned for my next blog on Machine Learning Tutorial . " 20

"Machine Learning ( ML ) is a specific subject within the broader AI arena , describing the ability for a machine to improve its ability by practicing a task or being exposed to large data sets . " 19 "Machine Learning requires a great deal of dedication and practice to learn , due to the many subtle complexities involved in ensuring your machine learns the right thing and not the wrong thing . " 19 "Overfitting is the result of focussing a Machine Learning algorithm too closely on the training data , so that it is not generalized enough to correctly process new data . " 19

"Machine learning is one of many subfields of artificial intelligence , concerning the ways that computers learn from experience to improve their ability to think , plan , decide , and act . " 18 "Many fields fall under the umbrella of AI , such as computer vision , robotics , machine learning , and natural language processing . " 18 "Machine learning is at the core of our journey towards artificial general intelligence , and in the meantime , it will change every industry and have a massive impact on our day - to - day lives . " 18

"Machine Learning systems are probabilistic : tasks are executed and decisions are made on incomplete information and outcomes are assigned probabilities of being correct . " 4 "For machine learning to gain wider adoption , these technologies need to be simplified and delivered as a service . " 4 "Built on Apache Spark , Watson Machine Learning intelligently and automatically builds models using open machine learning libraries and the most comprehensive set of algorithms in the industry . " 4

"With unsupervised learning , the machine is not given the target or correctly labeled data ; instead , it has to learn how to recognize patterns in the data itself and come up with groupings or classifications on its own . " 22 "With semi - supervised learning , the machine is given a subset of labeled data that is can use to discern and apply patterns to unlabeled data . " 22 "Machine learning is the process of teaching machines how to learn by providing them with guidance that helps them develop logic on their own and giving them access to datasets you want them to explore . " 22 "Other examples of artificial intelligence include robotics , speech recognition , and natural language generation , all of which also require some element of machine learning . " 22

"Everything begins with training a machine - learning model , a mathematical function capable of repeatedly modifying how it operates until it can make accurate predictions when given fresh data . " 15 "While training for more complex machine - learning models such as neural networks differs in several respects , it is similar in that it also uses a " gradient descent " approach , where the value of " weights " that modify input data are repeatedly tweaked until the output values produced by the model are as close as possible to what is desired . " 15 "Machine learning systems are used all around us , and are a cornerstone of the modern internet . " 15 "For firms that do n't want to build their own machine - learning models , the cloud platforms also offer AI - powered , on - demand services -- such as voice , vision , and language recognition . " 15

"There are many different reasons to implement machine learning and ways to go about it . " 22 "As with anything , there is evidence of other contributing factors and business drivers , but these three advances have clearly been dominant in terms of paving the way for accelerated use of machine learning and new and innovative applications of artificial intelligence . " 22 "Machine learning and artificial intelligence allow financial institutions to sift through data and find anomalies quickly , preventing illegal activity and saving potential company losses . " 22 "While self - driving cars are extremely complex machines , their Artificial Intelligence ( AI ) is powered by machine learning . " 22

"Machine learning is n't the same as Artificial Intelligence ( AI ) , but the line is starting to get a bit blurry with the applications . " 12 "As noted above , machine learning is the science of getting computers to come to conclusions based on information but without being specifically programmed in how to accomplish said task . " 12 "AI , on the other hand , is the science behind creating systems that either have , or appear to possess , human - like intelligence and process information in a similar manner . " 12 "Machine learning helps Google to not just understand where there are similarities in queries , but we can also see it determining that if I need my car fixed I may need a mechanic ( good call Google ) , whereas for replacing it I may be referring to parts or in need of governmental documentation to replace the entire thing . " 12

"AI initiates common sense , problem - solving and analytical reasoning power in machines , which is much difficult and a tedious job . " 34 "AI is achieved by analysing how the human brain works while solving an issue and then using that analytical problem - solving techniques to build complex algorithms to perform similar tasks . " 34 "Reinforcement learning assumes that a software agent i.e. a robot , or a computer program or a bot , connect with a dynamic environment to attain a definite goal . " 34

"Convolutional neural networks , or CNNs , are the variant of deep learning most responsible for recent advances in computer vision . " 36 "Machines with the dexterity and fine motor skills of a human are still a ways away . " 36 "From autonomous cars to multiplayer games , machine learning algorithms can now approach or exceed human intelligence across a remarkable number of tasks . " 36 "Policymakers need not wring their hands just yet about how intelligent machine learning may one day become . " 36

"To answer how AI works to simulate human intelligence , it is important to understand the concept of algorithms . " 6 "Machine Learning can be defined as a state when a software program is able to change its algorithms through data , without any human intervention while making predictions to get to the desired result . " 6 "Traditional algorithms rely solely on an " if " and " when " approach , this approach is what facilitates the creation of nearly all common software - powered devices we use today . " 6

"Supervised learning involves continually testing the bot with the data you have labelled with answers , until they can get it right with new data . " 31 "Unsupervised learning involves asking the bot to come up with its own answers or patterns based on the data you provide . " 31 "However , machine learning algorithms take a lot of effort to tune properly , require masses of data , and are a nightmare to debug . " 31

"Unsupervised learning refers to the training of an AI system using information that is not classified or labelled . " 25 "In unsupervised learning , an AI system is presented with unlabeled , uncategorized data and the system 's algorithms act on the data without prior training . " 25 "For unsupervised learning algorithms , the AI system is presented with an unlabeled and uncategorized data set . " 25

99 A direct measurement on how much interesting information the algorithm found through this source https://www.trendmicro.com/vinfo/us/security/definition/machine-learning/ 26
Machine Learning - Definition - Trend Micro USA
"Machine learning is more than just a buzz - word -- it is a technological tool that operates on the concept that a computer can learn information without human mediation . " 26
"With traditional machine learning , the computer learns how to decipher information as it has been labeled by humans -- hence , machine learning is a program that learns from a model of human - labeled datasets . " 26
"In unsupervised machine learning , the machine is able to understand and deduce patterns from data without human intervention . " 26
"With machine learning 's ability to catch such malware forms based on family type , it is without a doubt a logical and strategic cybersecurity tool . " 26
"Trend Micro 's Script Analyzer , part of the Deep Discovery(tm ) solution , uses a combination of machine learning and sandbox technologies to identify webpages that use exploits in drive - by downloads . " 26
"Machine learning uses the patterns that arise from data mining to learn from it and make predictions . " 26
"While others paint machine learning as a magical black box or a complicated mathematical system that can teach itself to generate accurate predictions from data with possible false positives , we at Trend Micro view it as one valuable addition to other techniques that make up our multi - layer approach to security . " 26
88 A direct measurement on how much interesting information the algorithm found through this source https://en.wikipedia.org/wiki/Machine_learning 8
Machine learning - Wikipedia
"Data mining uses many machine learning methods , but with different goals ; on the other hand , machine learning also employs data mining methods as " unsupervised learning " or as a preprocessing step to improve learner accuracy . " 8
"Generalization in this context is the ability of a learning machine to perform accurately on new , unseen examples / tasks after having experienced a learning data set . " 8
"Various processes , techniques and methods can be applied to one or more types of machine learning algorithms to enhance their performance . " 8
"Feature learning algorithms , also called representation learning algorithms , often attempt to preserve the information in their input but also transform it in a way that makes it useful , often as a pre - processing step before performing classification or predictions . " 8
"Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process . " 8
"Rule - based machine learning is a general term for any machine learning method that identifies , learns , or evolves " rules " to store , manipulate or apply knowledge . " 8
"Although machine learning has been transformative in some fields , machine - learning programs often fail to deliver expected results . " 8
"When trained on man - made data , machine learning is likely to pick up the same constitutional and unconscious biases already present in society . " 8
"Because of such challenges , the effective use of machine learning may take longer to be adopted in other domains . " 8
85 A direct measurement on how much interesting information the algorithm found through this source https://www.sas.com/en_us/insights/analytics/machine-learning.html 5
Machine Learning: What it is and why it matters | SAS
"Because of new computing technologies , machine learning today is not like machine learning of the past . " 5
"While artificial intelligence ( AI ) is the broad science of mimicking human abilities , machine learning is a specific subset of AI that trains a machine how to learn . " 5
"Machine learning can be used to achieve higher levels of efficiency , particularly when applied to the Internet of Things . " 5
"Machine learning has developed based on the ability to use computers to probe the data for structure , even if we do not have a theory of what that structure looks like . " 5
"Because machine learning often uses an iterative approach to learn from data , the learning can be easily automated . " 5
"Deep learning combines advances in computing power and special types of neural networks to learn complicated patterns in large amounts of data . " 5
"SAS graphical user interfaces help you build machine learning models and implement an iterative machine learning process . " 5
"From drilling holes to preventing health care fraud , learn about some of the new technologies SAS has patented with IoT and machine learning technologies . " 5
74 A direct measurement on how much interesting information the algorithm found through this source https://appen.com/machine-learning/ 22
Machine Learning Overview | What is Machine Learning?
"With unsupervised learning , the machine is not given the target or correctly labeled data ; instead , it has to learn how to recognize patterns in the data itself and come up with groupings or classifications on its own . " 22
"With semi - supervised learning , the machine is given a subset of labeled data that is can use to discern and apply patterns to unlabeled data . " 22
"Machine learning is the process of teaching machines how to learn by providing them with guidance that helps them develop logic on their own and giving them access to datasets you want them to explore . " 22
"Other examples of artificial intelligence include robotics , speech recognition , and natural language generation , all of which also require some element of machine learning . " 22
"There are many different reasons to implement machine learning and ways to go about it . " 22
"As with anything , there is evidence of other contributing factors and business drivers , but these three advances have clearly been dominant in terms of paving the way for accelerated use of machine learning and new and innovative applications of artificial intelligence . " 22
"Machine learning and artificial intelligence allow financial institutions to sift through data and find anomalies quickly , preventing illegal activity and saving potential company losses . " 22
"While self - driving cars are extremely complex machines , their Artificial Intelligence ( AI ) is powered by machine learning . " 22
"Use machine learning to build stronger underwriting models based on a wide variety of data points . " 22
"Reinforcement learning is the most abstract approach and based entirely on the machine , often referred to as the " learning agent " , learning through trial and error . " 22
"Through exploration and exploitation of its environment , the learning agent , fueled by advanced machine learning algorithms , ultimately gains enough knowledge to begin to demonstrate almost human - like levels of artificial intelligence . " 22
"Supervised and reinforcement learning are incredible tools that can be applied to gain insights and do more with unstructured data than ever before . " 22
"One reason is that for most machine learning models , you are trying to get a computer to make sense of a data - set with an incredible amount of variation . " 22
70 A direct measurement on how much interesting information the algorithm found through this source https://thenextweb.com/contributors/2018/11/30/how-to-get-a-job-working-with-artificial-intelligence-machine-learning/ 33
How to get a job working with artificial intelligence/machine learning
"Machine learning is a set of programming tools to work with data and deep learning or reinforcement learning is a subset within that . " 33
"Broadly speaking , if you want to develop your career in artificial intelligence , you can get started with a software development background and pick up the machine learning theory , or you can start off with the machine learning theory and communication skills and gradually pick up the programming chops to work in machine learning . " 33
"In practice , machine learning engineers will lean more on their software engineering chops , while data scientists rely more on their knowledge of machine learning theory and statistical inference , along with the ability to communicate those data insights . " 33
"You 'll start working with critical data science tools , such as Pandas and sci - kit learn , and get a real feel for how to put machine learning theory into practice . " 33
66 A direct measurement on how much interesting information the algorithm found through this source https://stackoverflow.com/questions/2620343/what-is-machine-learning 32
definition - What is machine learning? - Stack Overflow
"Machine learning is a field of computer science , probability theory , and optimization theory which allows complex tasks to be solved for which a logical / procedural approach would not be possible or feasible . " 32
"Machine learning is a methodology to create a model based on sample data and use the model to make a prediction or strategy . " 32
"Machine learning is simply a generic term to define a variety of learning algorithms that produce a quasi learning from examples ( unlabeled / labeled ) . " 32
"Machine learning is the study in computing science of making algorithms that are able to classify information they have n't seen before , by learning patterns from training on similar information . " 32
"Shamelessly ripped from Wikipedia : Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data , such as from sensor data or databases . " 32
"Basically , machine learning is a very wide - open discipline that contains many methods and algorithms that make it impossible for there to be 1 answer to your 3rd question . " 32
62 A direct measurement on how much interesting information the algorithm found through this source https://www.toptal.com/machine-learning/machine-learning-theory-an-introductory-primer 19
A Machine Learning Tutorial with Examples | Toptal
"Machine Learning ( ML ) is coming into its own , with a growing recognition that ML can play a key role in a wide range of critical applications , such as data mining , natural language processing , image recognition , and expert systems . " 19
"Neural networks are well suited to machine learning models where the number of inputs is gigantic . " 19
"Deep learning is a machine learning method that relies on artificial neural networks , allowing computer systems to learn by example . " 19
"Machine Learning ( ML ) is a specific subject within the broader AI arena , describing the ability for a machine to improve its ability by practicing a task or being exposed to large data sets . " 19
"Machine Learning requires a great deal of dedication and practice to learn , due to the many subtle complexities involved in ensuring your machine learns the right thing and not the wrong thing . " 19
"Overfitting is the result of focussing a Machine Learning algorithm too closely on the training data , so that it is not generalized enough to correctly process new data . " 19
59 A direct measurement on how much interesting information the algorithm found through this source https://www.zdnet.com/article/what-is-machine-learning-everything-you-need-to-know/ 15
What is machine learning? Everything you need to know | ZDNet
"Machine learning is enabling computers to tackle tasks that have , until now , only been carried out by people . " 15
"Machine learning may have enjoyed enormous success of late , but it is just one method for achieving artificial intelligence . " 15
"Alongside machine learning , there are various other approaches used to build AI systems , including evolutionary computation , where algorithms undergo random mutations and combinations between generations in an attempt to " evolve " optimal solutions , and expert systems , where computers are programmed with rules that allow them to mimic the behavior of a human expert in a specific domain , for example an autopilot system flying a plane . " 15
"However , Facebook 's approach of using publicly available data to train systems could provide an alternative way of training systems using billion - strong datasets without the overhead of manual labeling . " 15
"Were semi - supervised learning to become as effective as supervised learning , then access to huge amounts of computing power may end up being more important for successfully training machine - learning systems than access to large , labelled datasets . " 15
"Everything begins with training a machine - learning model , a mathematical function capable of repeatedly modifying how it operates until it can make accurate predictions when given fresh data . " 15
"While training for more complex machine - learning models such as neural networks differs in several respects , it is similar in that it also uses a " gradient descent " approach , where the value of " weights " that modify input data are repeatedly tweaked until the output values produced by the model are as close as possible to what is desired . " 15
"Machine learning systems are used all around us , and are a cornerstone of the modern internet . " 15
"For firms that do n't want to build their own machine - learning models , the cloud platforms also offer AI - powered , on - demand services -- such as voice , vision , and language recognition . " 15
49 A direct measurement on how much interesting information the algorithm found through this source https://www.mathworks.com/discovery/machine-learning.html 0
What Is Machine Learning? | How It Works, Techniques & Applications - MATLAB & Simulink
"Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals : learn from experience . " 0
"Machine learning algorithms use computational methods to " learn " information directly from data without relying on a predetermined equation as a model . " 0
"Machine learning algorithms find natural patterns in data that generate insight and help you make better decisions and predictions . " 0
"With tools and functions for handling big data , as well as apps to make machine learning accessible , MATLAB is an ideal environment for applying machine learning to your data analytics . " 0
"Integrate machine learning models into enterprise systems , clusters , and clouds , and target models to real - time embedded hardware . " 0
47 A direct measurement on how much interesting information the algorithm found through this source https://searchenterpriseai.techtarget.com/definition/machine-learning-ML 23
What is machine learning (ML)? - Definition from WhatIs.com
"Just as there are nearly limitless uses of machine learning , there is no shortage of machine learning algorithms . " 23
"As machine learning continues to increase in importance to business operations and AI becomes ever more practical in enterprise settings , the machine learning platform wars will only intensify . " 23
"In today 's world , every system that does well has a machine Learning algorithm at its heart . " 23
"Processes involved in machine learning are similar to that of data mining and predictive modeling . " 23
44 A direct measurement on how much interesting information the algorithm found through this source https://skymind.ai/wiki/ai-vs-machine-learning-vs-deep-learning 11
Artificial Intelligence (AI) vs. Machine Learning vs. Deep Learning | Skymind
"You can think of deep learning , machine learning and artificial intelligence as a set of Russian dolls nested within each other , beginning with the smallest and working out . " 11
"Deep learning is a subset of machine learning , and machine learning is a subset of AI , which is an umbrella term for any computer program that does something smart . " 11
"For example , symbolic logic - rules engines , expert systems and knowledge graphs - could all be described as AI , and none of them are machine learning . " 11
"In 1959 , Arthur Samuel , one of the pioneers of machine learning , defined machine learning as a " field of study that gives computers the ability to learn without being explicitly programmed . " 11
38 A direct measurement on how much interesting information the algorithm found through this source https://www.sap.com/products/leonardo/machine-learning/what-is-machine-learning.html 27
What is Machine Learning? | SAP
"Machine learning technology teaches computers how to perform tasks by learning from data a instead of being explicitly programmed . " 27
"Determine if machine learning technology is right for your company , and get practical guidance on how to build a smart AI strategy . " 27
"Machine learning can analyze big , complex , and streaming data , and find insights a including predictive insights a that are beyond human capabilities . " 27
"Manufacturers collect a huge amount of data from plant sensors and the Internet of Things a which is perfect for machine learning . " 27
37 A direct measurement on how much interesting information the algorithm found through this source https://www.paymentsjournal.com/how-machine-learning-works-and-why-its-important/ 16
How Machine Learning Works and Why It’s Important | PaymentsJournal
"This is due in part to amazing developments in machine learning , deep learning , and neural networks . " 16
"As you have most likely already gathered , machine learning is the branch of AI dedicated to endowing machines with the ability to learn . " 16
"Currently , machine learning applications allow for a machine to train in a certain task by analyzing examples of that task . " 16
31 A direct measurement on how much interesting information the algorithm found through this source https://becominghuman.ai/ai-machine-learning-deep-learning-explained-in-5-minutes-b88b6ee65846?gi=13730498ca24 37
AI, Machine Learning, & Deep Learning Explained in 5 Minutes
"Off late , though , " Machine Learning " and " Deep Learning " have surfaced , with many asking what exactly each of these are . " 37
"Machine Learning , at its most basic form , is the practice of using algorithms to parse data , learn from it , and then make a determination or prediction about something in the world . " 37
"Machine Learning , at its core , is really just making a line of best fit , except in many dimensions . " 37
"Latest News , Info and Tutorials on Artificial Intelligence , Machine Learning , Deep Learning , Big Data and what it means for Humanity . " 37
29 A direct measurement on how much interesting information the algorithm found through this source https://www.edureka.co/blog/what-is-machine-learning/ 20
What is Machine Learning? | Types of Machine Learning | Edureka
"Well , Machine Learning is a concept which allows the machine to learn from examples and experience , and that too without being explicitly programmed . " 20
"Machine Learning is a subset of artificial intelligence which focuses mainly on machine learning from their experience and making predictions based on its experience . " 20
"If you wanna learn about machine learning in depth , then stay tuned for my next blog on Machine Learning Tutorial . " 20
28 A direct measurement on how much interesting information the algorithm found through this source https://machinelearningmastery.com/how-machine-learning-algorithms-work/ 3
How Machine Learning Algorithms Work (they learn a mapping of input to output)
"Different machine learning algorithms make different assumptions about the shape and structure of the function and how best to optimize a representation to approximate it . " 3
"You also learned that different machine learning algorithms make different assumptions about the form of the underlying function . " 3
"Jason Brownlee , PhD is a machine learning specialist who teaches developers how to get results with modern machine learning methods via hands - on tutorials . " 3
"Sir , I need some basic operation of RBF kernel based learning and on Reproducing kernel hilbert spaces ( RKHS ) using GRAM Matrix along with their MATLAB implementation for my research work in Ph.D. Kindly guide me on above topics . " 3
27 A direct measurement on how much interesting information the algorithm found through this source https://medium.com/machine-learning-for-humans/why-machine-learning-matters-6164faf1df12 18
A Beginner’s Guide to AI/ML 🤖👶 – Machine Learning for Humans – Medium
"Machine learning is one of many subfields of artificial intelligence , concerning the ways that computers learn from experience to improve their ability to think , plan , decide , and act . " 18
"Many fields fall under the umbrella of AI , such as computer vision , robotics , machine learning , and natural language processing . " 18
"Machine learning is at the core of our journey towards artificial general intelligence , and in the meantime , it will change every industry and have a massive impact on our day - to - day lives . " 18
26 A direct measurement on how much interesting information the algorithm found through this source https://www.brookings.edu/research/what-is-machine-learning/ 36
What is machine learning? Search The Brookings Institution The Brookings Institution Search Menu Twitter The Brookings Institution Facebook Twitter Yo...
"Machine learning is now so popular that it has effectively become synonymous with artificial intelligence itself . " 36
"Indeed , machine learning is now so popular that it has effectively become synonymous with artificial intelligence itself . " 36
"With enough data , deep neural networks will almost always do the best job at estimating how likely something is . " 36
"When several leading researchers recently set a deep learning algorithm loose on Amazon reviews , they were surprised to learn that the algorithm had not only taught itself grammar and syntax , but a sentiment classifier too . " 36
"Convolutional neural networks , or CNNs , are the variant of deep learning most responsible for recent advances in computer vision . " 36
"Machines with the dexterity and fine motor skills of a human are still a ways away . " 36
"From autonomous cars to multiplayer games , machine learning algorithms can now approach or exceed human intelligence across a remarkable number of tasks . " 36
"Policymakers need not wring their hands just yet about how intelligent machine learning may one day become . " 36
24 A direct measurement on how much interesting information the algorithm found through this source https://martechtoday.com/how-machine-learning-works-150366 1
How Machine Learning Works, As Explained By Google - MarTech Today
"Data like this given to a machine learning system is often called a " training set " or " training data " because it 's used by the learner in the machine learning system to train itself to create a better model . " 1
"As said , it 's overkill for a teacher to use a machine learning system to predict test scores . " 1
"Google explained that you have to help add in some common sense rules , some human guidance that allows the machine learning process to understand how various objects might add up to an event . " 1
"But it 's staying pretty quiet on what exactly is going on with machine learning in search , to avoid giving away things it believes are pretty important and unique . " 1
24 A direct measurement on how much interesting information the algorithm found through this source https://www.fast.ai/2018/07/12/auto-ml-1/ 28
What do machine learning practitioners actually do? · fast.ai
"While many academic machine learning sources focus almost exclusively on predictive modeling , that is just one piece of what machine learning practitioners do in the wild . " 28
"People will sometimes describe machine learning as separate from data science , as though for machine learning , you can just begin with your nicely cleaned , formatted data set . " 28
23 A direct measurement on how much interesting information the algorithm found through this source https://www.ibmbigdatahub.com/blog/how-does-machine-learning-work 4
How does machine learning work? | IBM Big Data & Analytics Hub
"Machine Learning systems are probabilistic : tasks are executed and decisions are made on incomplete information and outcomes are assigned probabilities of being correct . " 4
"For machine learning to gain wider adoption , these technologies need to be simplified and delivered as a service . " 4
"Built on Apache Spark , Watson Machine Learning intelligently and automatically builds models using open machine learning libraries and the most comprehensive set of algorithms in the industry . " 4
18 A direct measurement on how much interesting information the algorithm found through this source https://www.makeuseof.com/tag/machine-learning-algorithms/ 9
What Are Machine Learning Algorithms? Here's How They Work make-use-of-logo logo-background menu search youtube google search-start close email facebo...
"Artificial intelligence and machine learning produce many of the advancements we see in the technology industry today . " 9
"Machine learning improves technology such as search engines , smart home devices , online services , and autonomous machines . " 9
"While people have long used Photoshop to create hoax images , machine learning takes this to a new level . " 9
"There are people working towards improving the safeguards around machine learning technology to prevent malicious use . " 9
18 A direct measurement on how much interesting information the algorithm found through this source https://www.searchenginejournal.com/how-machine-learning-in-search-works/257837/ 12
How Machine Learning in Search Works: Everything You Need to Know
"Machine learning is n't the same as Artificial Intelligence ( AI ) , but the line is starting to get a bit blurry with the applications . " 12
"As noted above , machine learning is the science of getting computers to come to conclusions based on information but without being specifically programmed in how to accomplish said task . " 12
"AI , on the other hand , is the science behind creating systems that either have , or appear to possess , human - like intelligence and process information in a similar manner . " 12
"Machine learning helps Google to not just understand where there are similarities in queries , but we can also see it determining that if I need my car fixed I may need a mechanic ( good call Google ) , whereas for replacing it I may be referring to parts or in need of governmental documentation to replace the entire thing . " 12
18 A direct measurement on how much interesting information the algorithm found through this source https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml 24
What is - Azure Machine Learning service | Microsoft Docs
"Use Machine Learning Studio when you want to experiment with machine learning models quickly and easily , and the built - in machine learning algorithms are sufficient for your solutions . " 24
17 A direct measurement on how much interesting information the algorithm found through this source https://www.google.com/about/main/machine-learning-qa/ 14
Breaking it down: A Q&A on machine learning | Google
"In practice , the patterns that the machine learns can be very complicated and hard to explain in words . " 14
"Thereas a whole host of new things Google is doing with machine learning , like Google Translate can take a photo of a street sign or menu in one language , figure out the words and language that are in the photo , and magically translate it real - time into your language . " 14
"And thatas what machine learning programs try to do , too : teach computers to learn from examples . " 14
"Speech recognition has made incredible advances in the last five years using sophisticated machine learning , and now you can use it to issue Google searches . " 14
17 A direct measurement on how much interesting information the algorithm found through this source https://www.marutitech.com/artificial-intelligence-and-machine-learning/ 34
Artificial intelligence and Machine learning made simple - Maruti Techlabs
"AI initiates common sense , problem - solving and analytical reasoning power in machines , which is much difficult and a tedious job . " 34
"AI is achieved by analysing how the human brain works while solving an issue and then using that analytical problem - solving techniques to build complex algorithms to perform similar tasks . " 34
"Reinforcement learning assumes that a software agent i.e. a robot , or a computer program or a bot , connect with a dynamic environment to attain a definite goal . " 34
16 A direct measurement on how much interesting information the algorithm found through this source https://www.digitaldoughnut.com/articles/2017/november/what-is-machine-learning-and-how-does-it-work 17
What Is Machine Learning And How Does It Work? - Digital Doughnut
"Machine Learning uses algorithms to create immersive , interactive experiences between technology and humans , transforming and personalizing our connection to technology by automating tasks that are typically repetitive , or tasks that we 're unable to do . " 17
15 A direct measurement on how much interesting information the algorithm found through this source https://hackernoon.com/what-is-machine-learning-how-does-it-work-13615bd20a89?gi=4b3eb014349a 6
What Is Machine Learning & How Does It Work? – Hacker Noon
"To answer how AI works to simulate human intelligence , it is important to understand the concept of algorithms . " 6
"Machine Learning can be defined as a state when a software program is able to change its algorithms through data , without any human intervention while making predictions to get to the desired result . " 6
"Traditional algorithms rely solely on an " if " and " when " approach , this approach is what facilitates the creation of nearly all common software - powered devices we use today . " 6
15 A direct measurement on how much interesting information the algorithm found through this source https://www.neurochaintech.io/what-is-machine-learning-neurochain/ 10
What is Machine Learning? And How Does It Work?
"In other words , machine learning occurs when computers are able to learn and improve upon algorithms without the need for human intervention . " 10
15 A direct measurement on how much interesting information the algorithm found through this source https://www.upgrad.com/blog/how-does-unsupervised-machine-learning-work/ 25
How does Unsupervised Machine Learning Work? | upGrad blog
"Unsupervised learning refers to the training of an AI system using information that is not classified or labelled . " 25
"In unsupervised learning , an AI system is presented with unlabeled , uncategorized data and the system 's algorithms act on the data without prior training . " 25
"For unsupervised learning algorithms , the AI system is presented with an unlabeled and uncategorized data set . " 25
"Clustering is one of the most important underlying concepts when it comes to unsupervised learning . " 25
"Association mining is not possible without clustering the data , and when you talk clustering , you talk unsupervised machine learning algorithm . " 25
15 A direct measurement on how much interesting information the algorithm found through this source https://www.burges-salmon.com/news-and-insight/blog-posts/ai-how-does-machine-learning-work/ 31
AI: how does machine learning work?
"Supervised learning involves continually testing the bot with the data you have labelled with answers , until they can get it right with new data . " 31
"Unsupervised learning involves asking the bot to come up with its own answers or patterns based on the data you provide . " 31
"However , machine learning algorithms take a lot of effort to tune properly , require masses of data , and are a nightmare to debug . " 31
14 A direct measurement on how much interesting information the algorithm found through this source https://www.cisco.com/c/en/us/products/security/machine-learning-security.html 30
What Is Machine Learning in Security? - Cisco Cisco.com Worldwide Search Log In Log Out Choose Language Selection View More Log In Log Out Choose Lang...
"This is where machine learning shines , because it can recognize patterns and predict threats in massive data sets , all at machine speed . " 30
13 A direct measurement on how much interesting information the algorithm found through this source https://www.economist.com/the-economist-explains/2015/05/13/how-machine-learning-works 13
How machine learning works - The Economist explains the economist down icon down icon user icon down icon magnifier icon hamburger icon close icon up ...
"Machine learning is exactly what it sounds like : an attempt to perform a trick that even very primitive animals are capable of , namely learning from experience . " 13
"Machine learning aims to help computers discover such fuzzy rules by themselves , without having to be explicitly instructed every step of the way by human programmers . " 13
10 A direct measurement on how much interesting information the algorithm found through this source https://towardsdatascience.com/how-does-machine-learning-work-6dd97f2be46c?gi=c08f7764a7b8 2
How does Machine Learning work? – Towards Data Science
"In practical terms , this means that the data scientist is making assumptions that a certain model or algorithm is the best one to fit the training data . " 2
10 A direct measurement on how much interesting information the algorithm found through this source https://www.expertsystem.com/how-does-machine-learning-work/ 7
How does machine learning work - Myth and reality
"Although there are several machine learning techniques , they all share a similar core composed of statistics and co - occurrences . " 7
"For machine learning systems , there simply are no tools with which to refine the algorithm . " 7
10 A direct measurement on how much interesting information the algorithm found through this source https://www.forbes.com/sites/forbestechcouncil/2018/07/11/machine-learning-vs-artificial-intelligence-how-are-they-different/ 21
Council Post: Machine Learning Vs. Artificial Intelligence: How Are They Different?
"Machine learning is technically a branch of AI , but it 's more specific than the overall concept . " 21
"Neural networks are a type of computer system that 's made to classify information like our own brains do . " 21
10 A direct measurement on how much interesting information the algorithm found through this source https://cloud.google.com/what-is-machine-learning/ 29
What is machine learning?  |  Cloud Machine Learning Services  |  Google Cloud
"In summary , wherever there is software that performs a labor - intensive task on a scale beyond human capability , machine learning may well be involved . " 29
10 A direct measurement on how much interesting information the algorithm found through this source https://www.computerworld.com/article/3007053/how-machine-learning-will-affect-your-business.html 35
How machine learning will affect your business | Computerworld
"Machine learning techniques may have been used for years , but recently there has been an explosion in their applications . " 35
"To make machine learning work for business , the algorithm needs to see lots and lots of examples of what it 's supposed to be doing . " 35

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