PRACTICAL RECOMMENDATION SYSTEMS - KIM FALK

Discover the fascinating world of recommendation systems with Kim Falk's book. Learn how the mechanisms work that suggest what to watch on Netflix, what to buy on Amazon, and what articles to read on your favorite news site. This book is a practical guide to creating and implementing recommendation systems, which will help you understand how to collect user data, generate personalized recommendations, and scale your solutions.

• Understanding the operation of recommendation systems
• Creating and implementing your own systems
• Collecting data about users
• Generating personalized recommendations
• Using popular recommendation algorithms
• Scaling recommendation systems
• Solving problems related to the expansion of systems

The book "Practical Recommendation Systems" is a comprehensive guide that will introduce you to the world of recommendation algorithms. The authors, Kim Falk, explain step by step how recommendation systems work, starting with basic information and ending with advanced issues of scaling and optimization. You will learn how to collect user data, analyze their preferences, and generate personalized recommendations that will increase the engagement and loyalty of your customers.

This publication is ideal for intermediate-level programmers who want to expand their knowledge in the field of databases and recommendation algorithms. You will find practical advice and examples that will help you create your own recommendation systems, tailored to the specifics of your business. Whether you work in e-commerce, social media, or the entertainment industry, this book will provide you with the necessary tools and knowledge to effectively use the potential of recommendation systems.

The PWN Scientific Publishing House, known for its high-quality scientific and educational publications, guarantees the reliability and timeliness of the presented information. The book was published in 2020 and contains 462 pages, format 234x164 mm, paperback. This is a solid dose of knowledge that will allow you to become an expert in the field of recommendation systems.