Introduction to Machine Learning, 2/e - 15 Angebote vergleichen

Lieferung aus: Vereinigte Staaten von Amerika, शिपिंग लागत के लिए: IND.
Von Händler/Antiquariat, Books WorldWide Express.
2nd ed.. Softcover. Brand New. “International Editionö - ISBN number and front cover may be different in rare cases but contents are same as the US edition. FOR MULTIPLE ORDERS AND EXPEDITE ORDERS, WE USE FEDEX/UPS/DHL SERVICE & RECEIVE FAST WITHIN 3-5 BUSINESS DAYS. No shipping to PO BOX, APO, FPO addresses. Kindly provide day time phone number in order to ensure smooth delivery. Printed in black & white in English language. Territorial restrictions may be printed on the book. We may ship from Asian regions for inventory purpose. 100% Customer satisfaction guaranteed! We use Fast Shipping via DHL/FEDEX/UPS.

Lieferung aus: Vereinigte Staaten von Amerika, शिपिंग लागत के लिए: IND.
Von Händler/Antiquariat, Textbooks Dealing.
Brand New. "International Edition". ISBN number and front cover may be different in rare cases but contents are same as the US edition. Printed in black & white in English language. Territorial restrictions may be printed on the book. For expedited shipping, Get it fast within 3-5 business days by FEDEX/UPS/DHL with Tracking Number. Kindly provide day time phone number in order to ensure smooth delivery. No shipping to PO BOX, APO, FPO addresses.We may ship from Asian regions for inventory purpose.100% Customer satisfaction guaranteed!

Lieferung aus: Vereinigte Staaten von Amerika, In Stock.
9780262325752,0262325756,introduction,machine,learning,ethem, A digital copy of "Introduction to Machine Learning" by Ethem Alpaydin. Download is immediately available upon purchase! eBook, Format: VitalSource. Type: . Copying: Allowed, .2Â.36 selections may be copied every 2Â.365 days. Printable: Allowed, .2Â.36 prints for 2Â.365 days. Expires: No Expiration. Read Aloud?: Allowed. Sharing: Not Allowed. Software: Online: No additional software required Offline: VitalSource Bookshelf. Shipping to USA only!

Lieferung aus: Indien, Usually dispatched within 1-2 business days, असली शिपिंग लागत अलग कर सकते हैं.
Von Händler/Antiquariat, MS Books World.
The main objective of machine learning is to program computers to utilize example data or previous experience to bring about a solution to a problem. Introduction To Machine Learning is a detailed textbook that covers a number of vital topics, which are not found in most introductory machine learning books. The author, Ethem Alpaydin, starts off by throwing light on several methods from fields such as pattern recognition, statistics, artificial intelligence, signal processing, data mining, neural networks and control. Alpaydin has also explained every learning algorithm, which helps the readers move easily from the equations present, to the computer program. In this new edition, Alpaydin has provided extensive coverage of three topics, which include graphical models, kernel methods and Bayesian estimation. In total, there are 19 chapters in this book, few of which include Combining Multuole Learners, Dimensionality Reduction, Nonparametric Methods, Hidden Markov Models and Reinforcement Learning. Through the course of this book, Alpaydin has provided detailed insights into the types of modelling and prediction issues dealt with, by machine learning. Alpaydin has also provided the readers with a brief overview of highly common paradigm families, algorithms and techniques in this field. This second edition of Introduction To Machine Learning was published by MIT in 2010 and is available in paperback. Key Features: The book targets those who are pursuing their postgraduate degrees in machine learning but is also useful for a beginner. It will also prove beneficial for engineers involved in the field of applying machine learning methods. Hardcover, संस्करण: 2, लेबल: Prentice Hall India Learning Private Limited, Prentice Hall India Learning Private Limited, उत्पाद समूह: Book, प्रकाशित: 2010, स्टूडियो: Prentice Hall India Learning Private Limited, बिक्री रैंक: 242170.

Lieferung aus: Indien, Usually dispatched within 6-10 business days, असली शिपिंग लागत अलग कर सकते हैं.
Von Händler/Antiquariat, Fast Media 2 ™.
The main objective of machine learning is to program computers to utilize example data or previous experience to bring about a solution to a problem. Introduction To Machine Learning is a detailed textbook that covers a number of vital topics, which are not found in most introductory machine learning books. The author, Ethem Alpaydin, starts off by throwing light on several methods from fields such as pattern recognition, statistics, artificial intelligence, signal processing, data mining, neural networks and control. Alpaydin has also explained every learning algorithm, which helps the readers move easily from the equations present, to the computer program. In this new edition, Alpaydin has provided extensive coverage of three topics, which include graphical models, kernel methods and Bayesian estimation. In total, there are 19 chapters in this book, few of which include Combining Multuole Learners, Dimensionality Reduction, Nonparametric Methods, Hidden Markov Models and Reinforcement Learning. Through the course of this book, Alpaydin has provided detailed insights into the types of modelling and prediction issues dealt with, by machine learning. Alpaydin has also provided the readers with a brief overview of highly common paradigm families, algorithms and techniques in this field. This second edition of Introduction To Machine Learning was published by MIT in 2010 and is available in paperback. Key Features: The book targets those who are pursuing their postgraduate degrees in machine learning but is also useful for a beginner. It will also prove beneficial for engineers involved in the field of applying machine learning methods. Hardcover, संस्करण: 2, लेबल: Prentice Hall India Learning Private Limited, Prentice Hall India Learning Private Limited, उत्पाद समूह: Book, प्रकाशित: 2010, स्टूडियो: Prentice Hall India Learning Private Limited, बिक्री रैंक: 242170.

Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, E-Book zum Download, Versandkostenfrei.
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods., Kindle Edition, Ausgabe: 3, Format: Kindle eBook, Label: The MIT Press, The MIT Press, Produktgruppe: eBooks, Publiziert: 2014-08-22, Freigegeben: 2014-08-22, Studio: The MIT Press, Verkaufsrang: 958661.

Lieferung aus: Deutschland, E-Book zum Download, Versandkostenfrei.
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods., Kindle Edition, Ausgabe: 3, Format: Kindle eBook, Label: The MIT Press, The MIT Press, Produktgruppe: eBooks, Publiziert: 2014-08-22, Freigegeben: 2014-08-22, Studio: The MIT Press, Verkaufsrang: 413455.

Lieferung aus: Deutschland, Free shipping.
Introduction to Machine Learning: The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning Bayesian decision theory parametric, semi-parametric, and nonparametric methods multivariate analysis hidden Markov models reinforcement learning kernel machines graphical models Bayesian estimation and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection ranking algorithms for perceptrons and support vector machines matrix decomposition and spectral methods distance estimation new kernel algorithms deep learning in multilayered perceptrons and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods. Englisch, Ebook.

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Lieferung aus: Vereinigte Staaten von Amerika, शिपिंग लागत के लिए: IND.
Von Händler/Antiquariat, Ergodebooks.
John Wiley & Sons. Hardcover. Used:Good.