My latest machine learning book has been published and will be available during the last week of July. From the back cover:
In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously.
On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem.
Link to the publisher page: https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-algorithms
Source code repository: https://github.com/PacktPublishing/Machine-Learning-Algorithms
Gitter chatroom: https://gitter.im/Machine-Learning-Algorithms/Lobby
These considerations may be accepted or not, however I hope to show some good starting points before beginning to study Machine Learning. [list_items][list_item]Old fashioned computing techniques are getting more and more useless. Industrial revolution is over and so all kind of merely-automatic machines.