Science Books
Free and open online science books and textbooks.
27 listings
Submitted Apr 23, 2017 to Science Books The book is available in hardcopy from Cambridge University Press. The publishers have kindly agreed to allow the online version to remain freely accessible.
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Submitted Apr 21, 2017 to Science Books CIML is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.). Its focus is on broad applications with a rigorous backbone. A subset can be used for an undergraduate course; a graduate course could probably cover the entire material and then some.
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Submitted Apr 20, 2017 to Science Books The book by Jure Leskovec, Anand Rajaraman, and Jeff Ullman is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining). The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explorations, most of the chapters are supplemented with further reading references. By agreement with the publisher, you can download the book for free.
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Submitted Apr 16, 2017 (Edited Apr 16, 2017) to Science Books After teaching software engineering for many years, I've been frustrated by the lack of a simple, concise, and practical introduction to the human aspects of software engineering for students interested in becoming software engineers.
In response, I've distilled my lectures from the past decade into these brief writings. They don't represent everything we know about software engineering (in particular, I don't discuss the deep technical contributions from the field), but the chapters do synthesize the broad evidence we have about how teams have to work together to succeed. |
Submitted Apr 16, 2017 (Edited Apr 16, 2017) to Science Books After teaching design for many years, I've been frustrated by the lack of a simple, concise, and practical introduction to design for technically-minded people.
In response, I've distilled my lectures from the past decade into these brief writings. They don't represent everything we know about design, and they certainly only represent my own technical stance on design, but my students have found them be accessible (mobile-friendly!) introductions to big ideas in design. |
Submitted Apr 13, 2017 (Edited Apr 13, 2017) to Science Books These notes are an attempt to extract essential machine learning concepts for beginners. They are a draft and will be updated. Likely they won’t be typos free for a while. They are dry and lack examples to complement and illustrate the general ideas. Notably, they also lack references, that will (hopefully) be added soon. The mathematical appendix is due to Andre Wibisono’s notes for the math camp of the 9.520 course at MIT.
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Submitted Mar 21, 2017 to Science Books The purpose of this book is to help to spread this knowledge among engineers who want to expand their wisdom in the exciting world of Machine Learning. I believe that anyone with an engineering background may find applications of Deep Learning, and Machine Learning in general, valuable to their work.
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Submitted Mar 20, 2017 to Science Books Immersive Linear Algebra is the world's first linear algebra book with fully interactive figures. After using linear algebra for 20 years times three persons, we were ready to write a linear algebra book that we think will make it substantially easier to learn and to teach linear algebra. In addition, the technology of mobile devices and web browsers have improved beyond a certain threshold, so that this book could be put together in a very novel and innovative way (we think). The idea is to start each chapter with an intuitive concrete example that practically shows how the math works using interactive illustrations. After that, the more formal math is introduced, and the concepts are generalized and sometimes made more abstract. We believe it is easier to understand the entire topic of linear algebra with a simple and concrete example cemented into the reader's mind in the beginning of each chapter.
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Submitted Feb 11, 2017 to Science Books Pulled from the web, here is a our collection of the best, free books on Data Science, Big Data, Data Mining, Machine Learning, Python, R, SQL, NoSQL and more.
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Submitted Feb 06, 2017 to Science Books James McCaffrey’s SciPy Programming Succinctly offers readers a quick, thorough grounding in knowledge of the Python open source extension SciPy. The SciPy library, accompanied by its interdependent NumPy, offers Python programmers advanced functions that work with arrays and matrices. Each section presents a complete demo program for programmers to experiment with, carefully chosen examples to best illustrate each function, and resources for further learning. Use this e-book to install and edit SciPy, and use arrays, matrices, and combinatorics in Python programming.
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Submitted Jan 27, 2017 to Science Books This is the open, online version of the book The Practice of Reproducible Research, to be published in print form by the University of California Press in 2017.
This book contains a collection of 31 case studies of reproducible research workflows, written by academic researchers in the data-intensive sciences. Each case study describes how the author combined specific tools, ideas, and practices in order to complete a real-world research project. Emphasis is placed on the practical aspects of how the author organized his or her research to make it as reproducible as possible. |
Submitted Jan 26, 2017 to Science Books The authors developed an introductory short course on qualitative research methods. This document provides an annotated version of the course material, which includes an overview of semi-structured interviews and focus groups, two techniques that are commonly used in policy research and applicable to many research questions.
The research described in this report was prepared for the U.S. Government by the RAND National Defense Research Institute. |
Submitted Jan 15, 2017 to Science Books This project began in the late 1980's as a means to supplement (or in some cases to largely replace ) the conventional textbook treatments of various topics in courses in General Chemistry and Environmental Chemistry. The motivation was in most cases to provide alternatives to what seem to be the rather shallow standardized treatments of certain topics presented in many commercial textbooks. The site contains reference text chapters, tutorials, advanced stuff, information for teachers, and more. By Stephen Lower at Simon Fraser University.
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Submitted Jan 15, 2017 to Science Books Thanks to special permission from Cambridge University Press, we are able to bring you, free, the complete Numerical Recipes books in C, Fortran 77, and Fortran 90 On-Line, in Adobe Acrobat format. Due to copyright restrictions, Numerical Recipes in C++ is not available as part of this free resource.
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Submitted Jan 15, 2017 to Science Books Game theory can be of considerable use to evolutionary biologists, especially behaviorists. Originally developed as a tool to predict rational human economic behavior, it has been successfully applied to many evolutionary problems. Game theory is useful in understanding situations where the fitness consequences of an individual's behavior depends in part on the types and frequencies of behaviors exhibited by other animals in the population. This site provides an introduction to evolutionary game theory. It is aimed primarily at undergraduates with a serious interest in animal behavior and evolution. I have tried to make the material accessible to any student with a good facility in algebra. Portions of the site dealing with the "war of attrition" do contain some calculus but I have taken care to explain the calculations in detail for students who have not yet studied calculus. By John Maynard Smith.
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Submitted Jan 02, 2017 to Science Books This introduction to LaTeX, a computer program for typesetting documents used by mathematicians, computer scientists, and many others, consists of webpages for each section and a downloadable PDF file. Written by David R. Wilkins at Trinity College Dublin.
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Submitted Dec 29, 2016 to Science Books Deep learning is not just the talk of the town among tech folks. Deep learning allows us to tackle complex problems, training artificial neural networks to recognize complex patterns for image and speech recognition. In this book, we'll continue where we left off in "Python Machine Learning" and implement deep learning algorithms in TensorFlow. By Sebastian Raschka.
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Submitted Dec 29, 2016 to Science Books The face of academia is changing. It is no longer sufficient to just publish or perish. We are now in an era where Twitter, Github, Figshare, and Alt Metrics are regular parts of the scientific workflow. Here Jeffrey Leek gives high level advice about which tools to use, how to use them, and what to look out for. This book is appropriate for scientists at all levels who want to stay on top of the current technological developments affecting modern scientific careers.
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Submitted Dec 29, 2016 to Science Books Draft of the lecture published in the Synthesis Lectures on Artificial Intelligence and Machine Learning series by Csaba Szepesvari (2009).
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Submitted Dec 29, 2016 to Science Books A concise overview of Python programming covering syntax, object oriented programming, modules, iterators and generators, and functional programming.
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