With the Statistics Playbook by Gary Sutton
This book will teach you how to use R in a different way than any other book out there. You will approach R concepts using publicly-available NBA statistical data rather than prepared datasets, and learn how to combine various methods and techniques.
Read on to learn more.
From Graph-Powered Machine Learning by Alessandro Negro
This article discusses managing data in graph-powered machine learning projects.
By Graph-Powered Machine Learning Alessandro Negro
This article discusses creating a bigraph for a user-item dataset.
From Ensemble Methods for Machine Learning by Gautam Kunapuli
Our first case study explores a medical decision-making task: breast cancer diagnosis. We will see how to use scikit-learn’s homogeneous parallel ensemble modules in practice. Specifically, we will train and evaluate the performance of three homogeneous parallel algorithms, each characterized by increasing randomness: bagging with decision trees, random forests and ExtraTrees.
By Douglas G. McIlwraith, Haralambos Marmanis, and Dmitry Babenko
In this article, excerpted from Algorithms of the Intelligent Web, Second Edition , we will talk about how we use classification everywhere.
By Douglas G. McIlwraith, Haralambos Marmanis, and Dmitry Babenko
In this article, excerpted from the book Algorithms of the Intelligent Web, we discuss classifications systems and their value for your applications.