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Paperback. Condition: New. Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms.
Paperback. Condition: New. Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms.
Seller: California Books, Miami, FL, U.S.A.
Condition: New.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: English
Published by O'Reilly Media, Inc, USA, 2017
ISBN 10: 1491924136 ISBN 13: 9781491924136
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Paperback. Condition: New. New copy - Usually dispatched within 4 working days.
Language: English
Published by O'Reilly Media 1/27/2017, 2017
ISBN 10: 1491924136 ISBN 13: 9781491924136
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condition: New. Thoughtful Machine Learning with Python: A Test-Driven Approach. Book.
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
First Edition
Condition: New. Featuring graphs and highlighted code throughout, Thoughtful Machine Learning with Python guides you through the process of writing problem-solving code, and in the process teaches you how to approach problems through scientific deduction and clever algorithms. Num Pages: 250 pages. BIC Classification: UMW; UYQM. Category: (P) Professional & Vocational. Dimension: 233 x 178 x 15. Weight in Grams: 666. . 2017. 1st Edition. Paperback. . . . .
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition.
Condition: New. Featuring graphs and highlighted code throughout, Thoughtful Machine Learning with Python guides you through the process of writing problem-solving code, and in the process teaches you how to approach problems through scientific deduction and clever algorithms. Num Pages: 250 pages. BIC Classification: UMW; UYQM. Category: (P) Professional & Vocational. Dimension: 233 x 178 x 15. Weight in Grams: 666. . 2017. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.
Language: English
Published by Oreilly & Associates Inc, 2017
ISBN 10: 1491924136 ISBN 13: 9781491924136
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 250 pages. 9.00x6.75x0.25 inches. In Stock.
Kartoniert / Broschiert. Condition: New. Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.Über den Autor.
Paperback. Condition: New. Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms.
Language: English
Published by O'reilly Media Feb 2017, 2017
ISBN 10: 1491924136 ISBN 13: 9781491924136
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Neuware - Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.
Paperback. Condition: New. Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms.
Language: English
Published by Oreilly & Associates Inc, 2017
ISBN 10: 1491924136 ISBN 13: 9781491924136
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 250 pages. 9.00x6.75x0.25 inches. In Stock. This item is printed on demand.