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

Markov chains - the multi-channel attribution model


A customer's journey undergoes a path of different channels before a purchase on an e-commerce website. Multi-channel attribution assigns a value to each step in the journey. The question is how one can identify the value in the actions people take on your website that lead to a conversion. Commonly, businesses use "last click" attribution, which means assigning all the conversion value to the last step in the journey or "first click" attribution. The first step in developing multi-channel attribution analytics is to understand the customer's journey - from awareness through purchase to after-purchase support. The ultimate goal is to develop loyal customers who spend a significant money on purchases, recommend the brand to others, and it potentially becomes a brand.

Getting ready

In order to perform a Markov chains multi-channel attribution model we shall be simulating customer journeys containing three unique channels.

How to do it...

Let...