Book Image

Machine Learning Algorithms

Book Image

Machine Learning Algorithms

Overview of this book

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. The algorithms that are covered in this book are linear regression, logistic regression, SVM, naïve Bayes, k-means, random forest, TensorFlow and feature engineering. In this book, you will how to use these algorithms to resolve your problems, and how they work. This book will also introduce you to natural language processing and recommendation systems, which help you to run multiple algorithms simultaneously. On completion of the book, you will know how to pick the right machine learning algorithm for clustering, classification, or regression for your problem
Table of Contents (22 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

References


  • Karteeka Pavan K., Allam Appa Rao, Dattatreya Rao A. V., and Sridhar G.R., Robust seed selection algorithm for k-means type algorithms, International Journal of Computer Science and Information Technology 3, no. 5 (October 30, 2011)
  • Shi J., Malik J., Normalized Cuts and Image Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22 (08/2000)
  • Von Luxburg U., A Tutorial on Spectral Clustering, 2007
  • Von Luxburg U., Cluster stability: an overview, arXiv 1007:1075v1, 7 July 2010