Books

4.2 (88 Ratings)?

Gaussian Processes for Machine Learning

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.

3.9 (88 Ratings)?

Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)

This is the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges.

4.1 (83 Ratings)?

Think Python 2nd Edition

This hands-on guide takes you through Python a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. Updated to Python 3.

3.5 (55 Ratings)?

Programming Pig

This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop.

3.9 (51 Ratings)?

Think Bayes: Bayesian Statistics Made Simple

Think Bayes is an introduction to Bayesian statistics using computational methods. The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics.

4.6 (50 Ratings)?

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition

4.0 (48 Ratings)?

Programming Computer Vision with Python

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, etc

4.3 (40 Ratings)?

Ecological Models and Data in R

The first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know to analyze their own data using the R language.

4.0 (39 Ratings)?

The Data Science Handbook

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

4.1 (37 Ratings)?

Data Mining with Rattle and R

This book aims to get you into data mining quickly. Load some data (e.g., from a database) into the Rattle toolkit and within minutes you will have the data visualised and some models built.