書籍詳細

書籍詳細




洋書

誰でもわかる機械学習

Machine Learning for Dummies

(--For Dummies.)

Mueller, John Paul   Massaron, Luca

For Dummies 2016/07
410 p. illustrations ; 24 cm.   
装丁: Pap   
版表示など: pap.    装丁について
テキストの言語: ENG    出版国: US
ISBN: 9781119245513
KCN: 1023895036
紀伊國屋書店 選定タイトル
標準価格:¥4,419(本体 ¥4,018)   
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納期について
DDC: 006.31
KDC: F88 データベース
関連書リスト: SB2849 データサイエンス 2017
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Annotation

Covering the entry-level topics needed to get you up and running with machine learning, this hands-on, friendly guide helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality.

Full Description

Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is.
Detailed information

Table of Contents

Introduction 1 Part 1: Introducing How Machines Learn 7 CHAPTER 1: Getting the Real Story about AI 9 CHAPTER 2: Learning in the Age of Big Data 23 CHAPTER 3: Having a Glance at the Future 35 Part 2: Preparing Your Learning Tools 45 CHAPTER 4: Installing an R Distribution 47 CHAPTER 5: Coding in R Using RStudio 63 CHAPTER 6: Installing a Python Distribution 89 CHAPTER 7: Coding in Python Using Anaconda 109 CHAPTER 8: Exploring Other Machine Learning Tools 137 Part 3: Getting Started with the Math Basics 145 CHAPTER 9: Demystifying the Math Behind Machine Learning 147 CHAPTER 10: Descending the Right Curve 167 CHAPTER 11: Validating Machine Learning 181 CHAPTER 12: Starting with Simple Learners 199 Part 4: Learning from Smart and Big Data 217 CHAPTER 13: Preprocessing Data 219 CHAPTER 14: Leveraging Similarity 237 CHAPTER 15: Working with Linear Models the Easy Way 257 CHAPTER 16: Hitting Complexity with Neural Networks 279 CHAPTER 17: Going a Step beyond Using Support Vector Machines 297 CHAPTER 18: Resorting to Ensembles of Learners 315 Part 5: Applying Learning to Real Problems 331 CHAPTER 19: Classifying Images 333 CHAPTER 20: Scoring Opinions and Sentiments 349 CHAPTER 21: Recommending Products and Movies 369 Part 6: The Part of Tens 383 CHAPTER 22: Ten Machine Learning Packages to Master 385 CHAPTER 23: Ten Ways to Improve Your Machine Learning Models 391 INDEX 399