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Tales of Science and Data

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This is an ebook written as a series of Jupyter notebooks, “intended as a collection of personally elaborated materials on Data Science. Topics span a quite large spectrum in the Data Science field: nothing will ever be fully comprehensive, but the purpose is keeping this continuously updated. Learning never ends!” Content includes: Probability & Statistics Machine Learning: Supervised Learning Unsupervised Learning Artificial Neural Networks Model Assessment Natural Language Processing Computer … Continue Reading

Python for Informatics: Exploring Information

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From Amazon: “This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet. It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh, and Linux computers. There are free downloadable copies of this book in various electronic … Continue Reading

Field Guide to Continuous Probability Distributions

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This compendium details hundred or so simple continuous probability distributions, their properties and their interrelations.

Efficient R Programming: A Practical Guide to Smarter Programming

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From Amazon: “There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin … Continue Reading

Machine Learning Cheat Sheet

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This cheat sheet contains many classical equations and diagrams on machine learning, which will help you quickly recall knowledge and ideas in machine learning.

Think Bayes

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Use your existing programming skills to learn and understand Bayesian statistics. Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing.

What Is Data Science?

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Why do we suddenly care about statistics and about data? This report examines the many sides of data science — the technologies, the companies and the unique skill sets.

Data Analysis for the Life Sciences

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Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst.

The Data Science Handbook

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The Data Science Handbook is a compilation of in-depth interviews with 25 remarkable data scientists, where they share their insights, stories, and advice.

The Art of Data Science

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This book describes, simply and in general terms, the process of analyzing data.