Seller: Amazing Books Pittsburgh, Pittsburgh, PA, U.S.A.
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Add to basketpaperback. Condition: Very Good. 2nd ed. Previous owner's markings on the blank page preceding the table of contents page. Text itself is unmarked. 3" x 4" crease on front cover. Light residue on top and bottom outside edge of pages.
Published by Packt Publishing 2020-01, 2020
ISBN 10: 1838820299 ISBN 13: 9781838820299
Language: English
Seller: Chiron Media, Wallingford, United Kingdom
PF. Condition: New.
Published by Packt Publishing 2018-08, 2018
ISBN 10: 1789347998 ISBN 13: 9781789347999
Language: English
Seller: Chiron Media, Wallingford, United Kingdom
PF. Condition: New.
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
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Add to basketCondition: New. Mastering Machine Learning Algorithms - Second Edition (Paperback or Softback) 2.97.
Published by Packt Publishing 8/30/2018, 2018
ISBN 10: 1789347998 ISBN 13: 9781789347999
Language: English
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
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Add to basketPaperback or Softback. Condition: New. Machine Learning Algorithms - Second Edition: Popular algorithms for data science and machine learning, 2nd Edition 1.96. Book.
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Add to basketCondition: New. 2018. Second. paperback. . . . . .
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Add to basketCondition: New. A new second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems, updated to include Python 3.8 and TensorFlow 2.x as well as the latest in new algorithms and techniques.
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Add to basketpaperback. Condition: Good. Cover is worn. Item has remainder mark. Paperback.
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Add to basketKartoniert / Broschiert. Condition: New. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. This book will act as an entry point for anyone who wants to make a career in Machine Learning. It covers algorithms like Linear regression.
Seller: Kennys Bookstore, Olney, MD, U.S.A.
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Add to basketCondition: New. 2018. Second. paperback. . . . . . Books ship from the US and Ireland.
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Add to basketCondition: Good. Corners are bent. Stains on outside cover/inside the book. Cover/Case has some rubbing and edgewear. Access codes, CDs, slipcovers and other accessories may not be included.
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
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Add to basketPAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithmsKey FeaturesExplore statistics and complex mathematics for data-intensive applicationsDiscover new developments in EM algorithm, PCA, and bayesian regressionStudy patterns and make predictions across various datasetsBook DescriptionMachine learning has gained tremendous popularity for its powerful and fast predictions with large datasets. However, the true forces behind its powerful output are the complex algorithms involving substantial statistical analysis that churn large datasets and generate substantial insight.This second edition of Machine Learning Algorithms walks you through prominent development outcomes that have taken place relating to machine learning algorithms, which constitute major contributions to the machine learning process and help you to strengthen and master statistical interpretation across the areas of supervised, semi-supervised, and reinforcement learning. Once the core concepts of an algorithm have been covered, you'll explore real-world examples based on the most diffused libraries, such as scikit-learn, NLTK, TensorFlow, and Keras. You will discover new topics such as principal component analysis (PCA), independent component analysis (ICA), Bayesian regression, discriminant analysis, advanced clustering, and gaussian mixture.By the end of this book, you will have studied machine learning algorithms and be able to put them into production to make your machine learning applications more innovative.What you will learnStudy feature selection and the feature engineering processAssess performance and error trade-offs for linear regressionBuild a data model and understand how it works by using different types of algorithmLearn to tune the parameters of Support Vector Machines (SVM)Explore the concept of natural language processing (NLP) and recommendation systemsCreate a machine learning architecture from scratchWho this book is forMachine Learning Algorithms is for you if you are a machine learning engineer, data engineer, or junior data scientist who wants to advance in the field of predictive analytics and machine learning. Familiarity with R and Python will be an added advantage for getting the best from this book.