Machine learning revised updated de alpaydin ethem (40 resultados)

Paperback. Condición: Good. A concise primer on machine learning?computer programs that learn from data and the basis of applications like voice recognition and driverless cars.No in-depth knowledge of math or programming required!Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition?as well as some we don?t yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of ?the new AI.? This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.Alpaydin explains that as Big Data has grown, the theory of machine learning?the foundation of efforts to process that data into knowledge?has also advanced. He covers:? The evolution of machine learning? Important learning algorithms and example applications? Using machine learning algorithms for pattern recognition? Artificial neural networks inspired by the human brain? Algorithms that learn associations between instances? Reinforcement learning? Transparency, explainability, and fairness in machine learning? The ethical and legal implicates of data-based decision makingA comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming?making it accessible for everyday readers and easily adoptable for classroom syllabi.…

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Paperback. Condición: Good. A concise primer on machine learning?computer programs that learn from data and the basis of applications like voice recognition and driverless cars.No in-depth knowledge of math or programming required!Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition?as well as some we don?t yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of ?the new AI.? This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.Alpaydin explains that as Big Data has grown, the theory of machine learning?the foundation of efforts to process that data into knowledge?has also advanced. He covers:? The evolution of machine learning? Important learning algorithms and example applications? Using machine learning algorithms for pattern recognition? Artificial neural networks inspired by the human brain? Algorithms that learn associations between instances? Reinforcement learning? Transparency, explainability, and fairness in machine learning? The ethical and legal implicates of data-based decision makingA comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming?making it accessible for everyday readers and easily adoptable for classroom syllabi.…

paperback. Condición: New.

paperback. Condición: Fine.

Paperback. Condición: Very Good. A concise primer on machine learningcomputer programs that learn from data and the basis of applications like voice recognition and driverless cars.No in-depth knowledge of math or programming required!Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognitionas well as some we dont yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.Alpaydin explains that as Big Data has grown, the theory of machine learningthe foundation of efforts to process that data into knowledgehas also advanced. He covers: The evolution of machine learning Important learning algorithms and example applications Using machine learning algorithms for pattern recognition Artificial neural networks inspired by the human brain Algorithms that learn associations between instances Reinforcement learning Transparency, explainability, and fairness in machine learning The ethical and legal implicates of data-based decision makingA comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programmingmaking it accessible for everyday readers and easily adoptable for classroom syllabi. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.…

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Paperback. Condición: New. A concise primer on machine learning-computer programs that learn from data and the basis of applications like voice recognition and driverless cars.No in-depth knowledge of math or programming required!Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition-as well as some we don't yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.Alpaydin explains that as Big Data has grown, the theory of machine learning-the foundation of efforts to process that data into knowledge-has also advanced. He covers. The evolution of machine learning. Important learning algorithms and example applications. Using machine learning algorithms for pattern recognition. Artificial neural networks inspired by the human brain. Algorithms that learn associations between instances. Reinforcement learning. Transparency, explainability, and fairness in machine learning. The ethical and legal implicates of data-based decision makingA comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming-making it accessible for everyday readers and easily adoptable for classroom syllabi.…

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Paperback or Softback. Condición: New. Machine Learning, Revised and Updated Edition. Book.

Paperback. Condición: new. Paperback. A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.MIT presents a concise primer on machine learning-computer programs that learn from data and the basis of applications like voice recognition and driverless cars.No in-depth knowledge of math or programming required!Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition-as well as some we don't yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.Alpaydin explains that as Big Data has grown, the theory of machine learning-the foundation of efforts to process that data into knowledge-has also advanced. He covers. The evolution of machine learning.Important learning algorithms and example applications.Using machine learning algorithms for pattern recognition.Artificial neural networks inspired by the human brain.Algorithms that learn associations between instances.Reinforcement learning.Transparency, explainability, and fairness in machine learning.The ethical and legal implicates of data-based decision makingA comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming-making it accessible for everyday readers and easily adoptable for classroom syllabi. "An updated introduction for generalists to this powerful technology, its applications and possible future directions"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Paperback. Condición: New.

Condición: New.

paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. Revised, Updated edition NO-PA16APR2015-KAP.

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Condición: New. 2021. Revised, Updated. Paperback. . . . . .

Condición: New. 2021. Revised, Updated. Paperback. . . . . . Books ship from the US and Ireland.

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Condición: New. In English.

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