Hands-On Recommendation Systems with Python: Start building powerful and personalized, recommendation engines with Python

Description

With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to desertcart. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains. If you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory. Review: A very good book - I like the way this book connects the theory part and the coding part. It not only helped me understand the concept in depth but also helped me get my hands dirty writing and executing the code. The book is well written and easy for anyone to read and understand. Would recommend buying this book if you want to have a good knowledge of recommendation systems. Review: Simple Introduction to the topic - Book is easy to understand and is methodically constructed. Prior experience in data science is needed, and for those experienced practitioners, this book is a good overview of the topic with code examples and real life data wrangling situations.