Computational and Inferential Thinking: The Foundations of Data Science
by Ani Adhikari, John DeNero
Publisher: GitBook 2017
Number of pages: 646
Data Science is about drawing useful conclusions from large and diverse data sets through exploration, prediction, and inference. Our primary tools for exploration are visualizations and descriptive statistics, for prediction are machine learning and optimization, and for inference are statistical tests and models.
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by Chris Bourke - University of Nebraska - Lincoln
A draft of text book for Computer Science I, covering CS1 topics in a generic manner using psuedocode with supplemental parts for specific languages. Computer Science is not programming. Programming is a necessary skill, but it is only the beginning.
by Eva Volna - Bookboon
This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.
by Brian Harvey - The MIT Press
This series is for people who are interested in computer programming because it's fun. The three volumes use the Logo as the vehicle for an exploration of computer science from the perspective of symbolic computation and artificial intelligence.
by Hans-Peter Bischof
This text is an introduction to the formal study of computation. The course will provide students with a broad perspective of computer science and will acquaint them with various formal systems on which modern computer science is based.