【Kinoppy】

「人工知能とデータサイエンス 2019/2020」(電子洋書)ご案内
Part 1.

 データの挑戦を見据えて、膨大な情報を効率的にフィルタリングし、解析し、可視化し、有意義な研究や意思決定、生産に結びつけていくために、どのようなリテラシーが求められているでしょうか?
 最近一年間の新刊・好評書目の中から、電子書籍でご利用頂けるタイトルをピックアップして3回に分けてご案内します。

Part 1. の今回は人工知能一般とデータサイエンス一般編(35点)です。
次回 Part 2. は10月18日、Part 3. は11月1日に ご案内する予定です。ご期待ください。

【2019年10月4日更新】

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1.人工知能一般

商品詳細へ金融の未来:フィンテック・AI・暗号の金融サービスへの影響
The Future of Finance : The Impact of FinTech, AI, and Crypto on Financial Services

Arslanian, Henri/ Fischer, Fabrice
紙版刊行: 2019/07
Palgrave Macmillan




This book, written jointly by an engineer and artificial intelligence expert along with a lawyer and banker, is a glimpse on what the future of the financial services will look like and the impact it will have on society.

商品詳細へ一冊でわかる人工知能
Artificial Intelligence : A Very Short Introduction (Very Short Introductions)

Boden, Margaret A.
紙版刊行: 2018/12
Oxford Univ Pr




This concise guide explains the history, theory, potential, application, and limitations of Artificial Intelligence. Boden shows how research into AI has shed light on the working of human and animal minds, and she considers the philosophical challenges AI raises: could programs ever be really intelligent, creative or even conscious?

商品詳細へCAPTCHAと人工知能の到達点と課題
The CAPTCHA - Perspectives and Challenges : Perspectives and Challenges in Artificial Intelligence (Smart Innovation, Systems and Technologies) Vol. 162

Brodic, Darko/ Amelio, Alessia
紙版刊行: 2019/10
Springer




This book discusses the CAPTCHA (completely automated public Turing test to tell computers and humans apart), an artificial-intelligence-based test commonly used on websites for preventing security attacks, covering its foundations, the main trends and challenges, as well as innovative features and research aspects.

商品詳細へ仮想人間:人工知能の現在と未来
Virtual Humans : Today and Tomorrow (Chapman & Hall/crc Artificial Intelligence and Robotics)

Burden, David/ Savin-Baden, Maggi
紙版刊行: 2019/02
Chapman & Hall




This book provides much needed definitions of what constitutes a ''virtual human'' and places them within a taxonomy of artificial intelligence. It explores the approaches to creating and using virtual humans, as well as issues such as embodiment, identity, and agency and their resulting ethical challenges.

商品詳細へ自動運転車と未来のモビリティ
Autonomous Vehicles and Future Mobility

Coppola, Pierluigi/ Esztergr-kiss, Domokos (EDT)
紙版刊行: 2019/06
Elsevier Science Ltd




Examines the long term effects on individuals, society, and on the environment of forthcoming transportation options.

商品詳細へ経営陣のためのAI・ビッグデータ・データサイエンス入門
An Introduction to Data : Everything You Need to Know About AI, Big Data and Data Science (Studies in Big Data)

Corea, Francesco
紙版刊行: 2019/01
Springer




Provides a first read and point of departure for executives who want to keep pace with the breakthroughs introduced by new analytical techniques and tremendous amounts of data.

商品詳細へマーケティング・販売・サービスにおけるAI入門
AI in Marketing, Sales and Service : How Marketers without a Data Science Degree Can Use AI, Big Data and Bots

Gentsch, Peter
紙版刊行: 2018/10
Palgrave Macmillan




This book provides an easy-to-understand guide to assessing the value and potential of AI and Algorithmics. It systematically draws together the technologies and methods of AI with clear business scenarios on an entrepreneurial level.

商品詳細へ石黒浩(大阪大学)共編/ジェミノイド研究:人間酷似遠隔操作型アンドロイド科学技術
Geminoid Studies : Science and Technologies for Humanlike Teleoperated Androids

Ishiguro, Hiroshi/ Libera, Fabio Dalla (EDT)
紙版刊行: 2018/05
Springer




This book describes the teleoperated android Geminoid, which has a very humanlike appearance, movements, and perceptions, requiring unique developmental techniques. The book faciliates understanding of the framework of android science and how to use it in real human societies.

商品詳細へソーシャル・ロボット:技術・社会・倫理的側面
Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction (Human-Computer Interaction Series)

Korn, Oliver (EDT)
紙版刊行: 2019/08
Springer




Provides an overview of social robots and underlying technologies like motion tracking or recognition of emotions and vital data.

商品詳細へトランスヒューマニズム・ハンドブック
The Transhumanism Handbook

Lee, Newton (EDT)
紙版刊行: 2019/07
Springer




人間を超える未来を夢見て、最先端テクノロジーと政治経済的な変革を結びつける、今日もっとも影響力の強いシリコンバレー的な思想の決定版見取図。 Transhumanism offers the most inclusive ideology for all ethnicities and races, the religious and the atheists, conservatives and liberals, the young and the old regardless of socioeconomic status, gender identity, or any other individual qualities. This book expounds on contemporary views and practical advice from more than 70 transhumanists.

商品詳細へ人工知能 vs. 人間知能
Artificial Intelligence versus Human Intelligence : Are Humans Going to Be Hacked?

Lexcellent, Christian
紙版刊行: 2019/06
Springer




人間はハックされるのか?ポピュラーサイエンス話題書。

商品詳細へAIを活用した問題解決:50の成功企業に学ぶ
Artifical Intelligence in Practice : How 50 Successful Companies Used Artificial Intelligence to Solve Problems

Marr, Bernard
紙版刊行: 2019/04
Wiley




This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others.

商品詳細へ人間の学習を促進させる人工知能
Artificial Intelligence Accelerates Human Learning : Discussion Data Analytics

Nagao, Katashi
紙版刊行: 2019/03
Springer




Focusing on students' presentations and discussions in laboratory seminars, this book presents case studies on evidence-based education using artificial intelligence (AI) technologies.

商品詳細へAI幻想
The AI Delusion

Smith, Gary
紙版刊行: 2018/10
Oxford Univ Pr




Gary Smith argues that the real danger of artificial intelligence is not that computers are smarter than us, but that we think they are. Through many examples, Smith shows that human reasoning is fundamentally different from artificial intelligence, and it is needed more than ever. Gary Smith is the Fletcher Jones Professor of Economics at Pomona College.

商品詳細へAI規制論
Robot Rules : Regulating Artificial Intelligence

Turner, Jacob
紙版刊行: 2018/11
Palgrave Macmillan




This book explains why AI is unique, what legal and ethical problems it could cause, and how we can address them.

2.データサイエンス一般

商品詳細へビジネスと意思決定のためのデータサイエンス
Data Science for Business and Decision Making

Favero, Luiz Paulo/ Belfiore, Patricia
紙版刊行: 2019/04
Academic Pr




This book covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work.

商品詳細へ計量投資におけるビッグデータと機械学習
Big Data and Machine Learning in Quantitative Investment (Wiley Finance)

Guida, Tony
紙版刊行: 2019/02
Wiley




The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning.

商品詳細へデータ可視化と知識工学
Data Visualization and Knowledge Engineering : Spotting Data Points with Artificial Intelligence (Lecture Notes on Data Engineering and Communications Technologies)

Hemanth, Jude/ Bhatia, Madhulika/ Geman, Oana (EDT)
紙版刊行: 2019/10
Springer




This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples.

商品詳細へデータサイエンスの実務:いかにデータを情報、よりよき意思決定、より強固な組織に結びつけるか
Real Work of Data Science : How to Turn Data into Information, Better Decisions, and Stronger Organizations

Kenett, Ron S./ Redman, Thomas C.
紙版刊行: 2019/04
Wiley




This book builds on contributions of Box, Deming, Tukey and others and explores the growing, role of predictive analytics, big data and modeling in marketing, healthcare and advanced manufacturing applications and the critical role that sound statistical reasoning can play in everyday work.

商品詳細へデータサイエンスのための特徴抽出・選択:予測モデルへの実践的アプローチ
Feature Engineering and Selection : A Practical Approach for Predictive Models (Chapman & Hall/crc Data Science)

Kuhn, Max/ Johnson, Kjell
紙版刊行: 2019/08
Chapman & Hall




This book describes techniques for finding the best representations of predictors for modeling the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

商品詳細へPython とRで基礎から学ぶデータサイエンス
Data Science Using Python and R (Wiley Series on Methods and Applications in Data Mining)

Larose, Chantal D./ Larose, Daniel T.
紙版刊行: 2019/05
Wiley




An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Exciting new topics such as random forests and general linear models are included. The book emphasizes datadriven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. It exercises at the end of every chapter, totaling over 500 exercises in the book.

商品詳細へソーシャルメディアのためのデータ解析入門
Social Media Measurement and Management : Entrepreneurial Digital Analytics

Lipschultz, Jeremy Harris
紙版刊行: 2019/07
Routledge




This textbook applies a critical and practical lens to the world of social media analytics.

商品詳細へデータの価値創出:予測アナリティクスの応用(テキスト)
Applying Predictive Analytics : Finding Value in Data

McCarthy, Richard V./ McCarthy, Mary M./ Ceccucci, Wendy
紙版刊行: 2019/05
Springer




This textbook focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software.

商品詳細へRグラフィックス(第3版)
R Graphics (Chapman & Hall/crc, the R) 3RD

Murrell, Paul
紙版刊行: 2018/11
Chapman & Hall




This is a major update, with a complete overhaul in focus and scope. It will now focus primarily on the two core graphics packages in R - graphics and grid - and has a new section on integrating graphics.

商品詳細へRユーザーのためのSAS:データサイエンスのための手引き
SAS for R Users : A Book for Data Scientists

Ohri, Ajay
紙版刊行: 2019/11
Wiley




Using a clear, step-by-step approach, this book presents an analytics workflow that mirrors that of the everyday data scientist. This up-to-date guide is compatible with the latest R packages as well as SAS University Edition.

商品詳細へデータサイエンスのためのメタ解析
Meta-analytics : Consensus Approaches and System Patterns for Data Analysis

Simske, Steven
紙版刊行: 2019/03
Morgan Kaufmann Pub




This book supplies an exhaustive set of patterns for data science to use on any machine learning based data analysis task. The book is 'meta' to analytics, and so covers general analytics in sufficient detail for the reader to engage with and understand hybrid or meta- approaches. The title has relevance to machine translation, robotics, biological and social sciences, medical and healthcare informatics, economics, business and finance.

商品詳細へデータサイエンス9つの落とし穴
The 9 Pitfalls of Data Science

Smith, Gary/ Cordes, Jay
紙版刊行: 2019/09
Oxford Univ Pr




Including plentiful real-world examples of data science triumphs and failures, this book exhibits from contemporary data scientists, such as Johan Ioannidis, the 'godfather to the science reform crowd'.

商品詳細へアルゴリズムの基礎:PythonとC#による実践的アプローチ(第2版)
Essential Algorithms : A Practical Approach to Computer Algorithms Using Python and C# 2ND

Stephens, Rod
紙版刊行: 2019/07
Wiley




In addition to describing algorithms and approaches, the author offers details on how to analyze the performance of algorithms. The book is filled with exercises that can be used to explore ways to modify the algorithms in order to apply them to new situations.

商品詳細へ『科学技術計算のためのPython : 確率・統計・機械学習』(原書)第2版
Python for Probability, Statistics, and Machine Learning 2ND

Unpingco, José
紙版刊行: 2019/07
Springer




This textbook, fully updated to feature Python version 3.7, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/ IPython notebooks, which are provided as supplementary downloads.

商品詳細へ『R言語徹底解説』(原書)第2版
Advanced R (Chapman & Hall/crc: R Series) 2ND

Wickham, Hadley
紙版刊行: 2019/06
Chapman & Hall




With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R.

商品詳細へデータマイニング・機械学習のためのアルゴリズム入門
Introduction to Algorithms for Data Mining and Machine Learning

Yang, Xin-she
紙版刊行: 2019/06
Academic Pr




Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages.

3.まずはここから! AI・データサイエンス既刊ベストセラー&ロングセラー

商品詳細へ統計学教育研究国際ハンドブック
International Handbook of Research in Statistics Education (Springer International Handbooks of Education)

Ben-Zvi, Dani/ Makar, Katie/ Garfield, Joan (EDT)
紙版刊行: 2018/01
Springer




「データサイエンス」時代に求められる統計学の教育と研究にたずさわる多数の世界的な専門家を結集して、過去・現在・未来を通して重要な論点を網羅する、包括的なリサーチマップ。不確実性、統計的推論、教師教育、カリキュラム、テクノロジーの利用、学習環境の整備、成績評価など。

商品詳細へ『統計学:Rを用いた入門書 改訂第2版』(原書)
Statistics : An Introduction Using R 2ND

Crawley, Michael J.
紙版刊行: 2014/11
Wiley




邦訳:2016年4月・共立出版。 This new edition of a bestselling title offers a concise introduction to a broad array is elementary enough to appeal to a wide range of disciplines.

商品詳細へ統計学・社会科学・生医学のための因果推論入門
Causal Inference for Statistics, Social, and Biomedical Sciences : An Introduction

Imbens, Guido W./ Rubin, Donald B.
紙版刊行: 2015/05
Cambridge Univ Pr




In this groundbreaking text, two world-renowned experts lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher. Winner, 2016 PROSE Award for Textbook, Social Sciences.

商品詳細へ統計学的再考:RとStanで学ぶベイズ統計学(テキスト)
Statistical Rethinking : A Bayesian Course with Examples in R and Stan (Chapman & Hall/crc Texts in Statistical Science)

Mcelreath, Richard
紙版刊行: 2015/12
Chapman & Hall




This book provides a more elementary introduction to Bayesian analysis than the Gelman book and is more suitable for graduate students in disciplines other than statistics.