Kumar Ashish. - Learning Predictive Analytics with Python

Data science is changing the way we go about our daily lives at an unprecedented pace. The recommendations you see on e-commerce websites, the technologies that prevent credit card fraud, the logic behind airline itinerary and route selections, the products and discounts you see in retail stores, and many more decisions are largely powered by data science. Futuristic sounding applications like self-driving cars, robots to do household chores, smart wearable technologies, and so on are becoming a reality, thanks to innovations in data science.

Predictive analytics is a branch of data science, used to predict unknown future events based on historical data. It uses a number of techniques from data mining, statistical modelling and machine learning to help make forecasts with an acceptable level of reliability.

Python is a high-level, object-oriented programming language. It has gained popularity because of its clear syntax and readability, and beginners can pick up the language easily. It comes with a large library of modules that can be used to do a multitude of tasks ranging from data cleaning to building complex predictive modelling algorithms.

I'm a co-founder at Tiger Analytics, a firm specializing in providing data science and predictive analytics solutions to businesses. Over the last decade, I have worked with clients at numerous Fortune 100 companies and start-ups alike, and architected a variety of data science solution frameworks. Ashish Kumar, the author of this book, is currently a budding data scientist at our company. He has worked on several predictive analytics engagements, and understands how businesses are using data to bring in scientific decision making to their organizations. Being a young practitioner, Ashish relates to someone who wants to learn predictive analytics from scratch. This is clearly reflected in the way he presents several concepts in the book.

Whether you are a beginner in data science looking to build a career in this area, or a weekend enthusiast curious to explore predictive analytics in a hands-on manner, you will need to start from the basics and get a good handle on the building blocks. This book helps you take the first steps in this brave new world; it teaches you how to use and implement predictive modelling algorithms using Python. The book does not assume prior knowledge in analytics or programming. It differentiates itself from other such programming cookbooks as it uses publicly available datasets that closely represent data encountered in business scenarios, and walks you through the analysis steps in a clear manner.

There are nine chapters in the book. The first few chapters focus on data exploration and cleaning. It is written keeping beginners to programming in mindby explaining different data structures and then going deeper into various methods of data processing and cleaning. Subsequent chapters cover the popular predictive modelling algorithms like linear regression, logistic regression, clustering, decision trees, and so on. Each chapter broadly covers four aspects of the particular modelmath behind the model, different types of the model, implementing the model in Python, and interpreting the results.

Statistics/math involved in the model is clearly explained. Understanding this helps one implement the model in any other programming language. The book also teaches you how to interpret the results from the predictive model and suggests different techniques to fine tune the model for better results. Wherever required, the author compares two different models and explains the benefits of each of the models. It will help a data scientist narrow down to the right algorithm that can be used to solve a specific problem. In addition, this book exposes the readers to various Python libraries and guides them with the best practices while handling different datasets in Python.

I am confident that this book will guide you to implement predictive modelling algorithms using Python and prepare you to work on challenging business problems involving data. I wish this book and its author Ashish Kumar every success.

Pradeep Gulipalli

Co-founder and Head of India Operations - Tiger Analytics