Book Image

Learning Predictive Analytics with Python

By : Ashish Kumar, Gary Dougan
Book Image

Learning Predictive Analytics with Python

By: Ashish Kumar, Gary Dougan

Overview of this book

Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You’ll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world.
Table of Contents (19 chapters)
Learning Predictive Analytics with Python
Credits
Foreword
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
A List of Links
Index

Acknowledgments

I dedicate this book to my beloved grandfather who is the prime reason behind whatever I am today. He is my source of inspiration and he is the one I want to be like. Not a single line of this book was written without thinking about him; may you stay strong and healthy.

I want to acknowledge the support of my family, especially my parents and siblings. My conversations with them were the power source, which kept me going.

I want to acknowledge the guidance and support of my friends for insisting that I should do this when I was skeptical about taking this up. I would like to thank Ajit and Pranav for being the best friends one could ask for and always being there for me. A special mention to Vijayaraghavan for lending his garden for me to work in and relax post the long writing sessions. I would like to thank my college friends, especially my wing mates, Zenithers, who have always been pillars of support. My friends at the Young India Fellowship have made me evolve as a person and I am grateful to all of them.

I would like to thank my college friends, especially my wing mates, Zenithers, who have been pillars of support all throughout my life. My friends at the Young India Fellowship have made me evolve as a person and I am grateful to all of them.

I would like to extend my sincere gratitude to my faculty and well wishers at IIT Madras and the Young India Fellowship. The Tiger Analytics family, especially Pradeep, provided a conducive environment and encouraged me to take up and complete this task. I would also like to convey my sincere regards to Zeena Johar for believing in me and giving me the best learning and working opportunities, which were more than what I could have asked for in my first job.

I want to thank my editors Nikhil, Amey, Saurabh, Indrajit, and reviewer, Matt, for their wonderful comments and prompt responses. I would like to thank the entire PACKT publication team that was involved with ISBN B01782.