Artificial Intelligence : A Very Short Introduction （Very Short Introductions）
Boden, Margaret A.
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?
Virtual Humans : Today and Tomorrow （Chapman & Hall/crc Artificial Intelligence and Robotics）
Burden, David/ Savin-Baden, Maggi
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.
Autonomous Vehicles and Future Mobility
Coppola, Pierluigi/ Esztergr-kiss, Domokos （EDT）
Elsevier Science Ltd
Examines the long term effects on individuals, society, and on the environment of forthcoming transportation options.
Geminoid Studies : Science and Technologies for Humanlike Teleoperated Androids
Ishiguro, Hiroshi/ Libera, Fabio Dalla （EDT）
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.
The Transhumanism Handbook
Lee, Newton （EDT）
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.
The AI Delusion
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.
Data Science for Business and Decision Making
Favero, Luiz Paulo/ Belfiore, Patricia
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.
Big Data and Machine Learning in Quantitative Investment （Wiley Finance）
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.
Data Science Using Python and R （Wiley Series on Methods and Applications in Data Mining）
Larose, Chantal D./ Larose, Daniel T.
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.
Applying Predictive Analytics : Finding Value in Data
McCarthy, Richard V./ McCarthy, Mary M./ Ceccucci, Wendy
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.
R Graphics （Chapman & Hall/crc, the R） 3RD
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.
SAS for R Users : A Book for Data Scientists
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.
Meta-analytics : Consensus Approaches and System Patterns for Data Analysis
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.
The 9 Pitfalls of Data Science
Smith, Gary/ Cordes, Jay
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'.
|『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
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.
Advanced R （Chapman & Hall/crc: R Series） 2ND
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.
Statistics : An Introduction Using R 2ND
Crawley, Michael J.
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.
Causal Inference for Statistics, Social, and Biomedical Sciences : An Introduction
Imbens, Guido W./ Rubin, Donald B.
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.