February 1

Free Data Science eBooks – February 2017

Ebooks, Blog, Resources

0  comments

Every month we scour the internet seeking out free eBooks to help you on your educational journey, and this month has been no different.

I hope these books prove to be a valuable resource to you and that you will visit regularly (and invite your friends too).

More...

If you haven't subscribed to our newsletter yet, why not subscribe using the form on the right - you'll be the very first to know when new resources are published.

3 Free Data Science Ebooks for February

This month, we have a book about Text Mining, one about Statistics and one about Artificial Intelligence. They're all FREE, so help yourself...

Enjoy!

Disclosure: The FREE ebooks were free to download at the time of posting but other links in this post may contain affiliate links. As Amazon Associates we may earn from qualifying purchases.

​​You can find further details in our TCs

Theory and Applications of Advanced Text Mining

Due to the growth of computer technologies and web technologies, we can easily collect and store large amounts of text data in the belief that these data contain useful knowledge.

Text mining techniques have been studied aggressively in order to extract the knowledge from the data since the late 1990s. Even if many important techniques have been developed, the text mining research field continues to expand for the needs arising from various application fields. This book is composed of 9 chapters introducing advanced text mining techniques. There are various techniques from relation extraction to under or less resourced language.

This book will give new knowledge in the text mining field and help many readers open new research fields.

Related Books

Introduction to Statistical Throught

The book is intended as an upper level undergraduate or introductory graduate textbook in statistical thinking with a likelihood emphasis for students with a good knowledge of calculus and the ability to think abstractly. "Statistical thinking" means a focus on ideas that statisticians care about as opposed to technical details of how to put those ideas into practice. The book does contain technical details, but they are not the focus. "Likelihood emphasis" means that the likelihood function and likelihood principle are unifying ideas throughout the text.

Another unusual aspect is the use of statistical software as a pedagogical tool. That is, instead of viewing the computer merely as a convenient and accurate calculating device, the book uses computer calculation and simulation as another way of explaining and helping readers understand the underlying concepts. The book is written with the statistical language R embedded throughout.

Related Books

Reinforcement Learning: An Introduction

by Richard S. Sutton and Andrew G. Barto

Reinforcement Learning : An introduction

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment.

In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.

The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

Related Books

Related Udemy Video Courses

Below are a few related Udemy courses that we recommend. They are by no means the only ones - there are LOADS more, and if these don't tickle your fancy, just click through. I'm sure you'll find something that does.

*NOTE - the prices listed below are the full price, and are not automatically updated when a sale is on. If you want to find out the sale price (often around 10 £/$/Euro), just click through!

Check out our free data science ebooks for February

Pin it for later

Need to save this for later?


Pin it to your favourite board  and you can get back to it when you're ready.


Tags

data science, free ebooks, statistics


You may also like

Awesome Gifts for Data Scientists

Computational Statistics is the New Holy Grail – Experts

3 Crucial Tips for Data Processing and Analysis

Free Must-Read Statistics Books for Aspiring Data Scientists

Correlation Is Not Causation – Pirates Prove It!

Fantastic Free Data Science Books for Aspiring Data Scientists

Free Data Science eBooks – April 2021

Free Data Science eBooks – March 2021

0 0 vote
Article Rating
Subscribe
Notify of
guest

This site uses Akismet to reduce spam. Learn how your comment data is processed.

0 Comments
Inline Feedbacks
View all comments
{"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}

Machine Learning Models:

The Big Picture

FREE Ultra HD pdf

Download your FREE mind map to learn about the different types of ML models in Machine Learning.

Chi-Squared Innovations
0
Would love your thoughts, please leave a comment!x
()
x