July 2018
Beginner to intermediate
146 pages
3h 39m
English
Overview
In "Hands-On Recommendation Systems with Python," you'll discover how to create effective recommendation engines using Python. This book offers practical guidance on building systems that provide personalized recommendations for movies, products, and more, enabling you to apply advanced techniques without delving into heavy theory.
What this Book will help me do
- Understand the key types of recommendation systems and their applications in various domains.
- Learn to manipulate and preprocess data effectively using the pandas Python library.
- Build a content-based recommenders using metadata to suggest personalized experiences.
- Gain proficiency in collaborative filtering techniques that analyze users' behavioral data.
- Combine diverse approaches to create robust hybrid recommendation systems.
Author(s)
None Banik is an experienced software developer and educator specializing in Python and data-driven solutions. With a pragmatic approach to explaining technical concepts, Banik focuses on hands-on projects that empower learners to build practical applications.
Who is it for?
This book is targeted at Python developers interested in building recommendation systems for scenarios such as social networking, e-commerce, or news personalization. It suits those with a basic understanding of Python and machine learning fundamentals, though advanced knowledge is not required. The book is particularly valuable for developers seeking to create practical, effective solutions for user personalization. Whether you're starting in the field or looking to enhance your existing skills, you'll find actionable insights and techniques here.
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