Book Image

Practical Machine Learning Cookbook

By : Atul Tripathi
Book Image

Practical Machine Learning Cookbook

By: Atul Tripathi

Overview of this book

Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations. The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more. The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.
Table of Contents (21 chapters)
Practical Machine Learning Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
14
Case Study - Forecast of Electricity Consumption

Vector quantization - image clustering


The development of technology in the field of digital media generates huge amounts of non-textual information in the form of images. If programs could comprehend the significance of these images and understand what they mean, this could result in a vast number of different applications. One such application could be the use of robots to extract malign tissue from hospital patients using body scan images to interpret the location of the tissue. Images are considered one of the most important media for conveying information. The potential for the retrieval of information is vast, so much so that users may be overwhelmed by the sheer amount of information retrieved. The unstructured format of images challenges classification and clustering techniques. Machine learning algorithms are used to extract information to understand images. One of the first steps towards understanding images is to segment them and identify the different objects within them. To...