Building Recommender Systems with Machine Learning and AI
Get started with building intelligent recommender systems
Created by Frank Kane
Discover how to create intelligent recommendation systems using Python, machine learning, and AI. Explore practical techniques behind content suggestions like those on Netflix and YouTube, and learn to build your own models from scratch. Gain hands-on experience with real-world data and modern algorithms.
Packt | Sep 2018 | 684 min
What You Will Learn
You'll start by exploring the foundations of recommender systems and gradually move into advanced topics like deep learning and hybrid models. Through hands-on coding exercises and real-world case studies, you'll apply each concept directly, reinforcing your understanding as you progress.
Key Features
- Build recommendation engines using collaborative, content-based, and hybrid methods
- Apply deep learning and AI to improve the accuracy of your recommendations
- Scale your solutions for large datasets using Apache Spark and advanced techniques
Target Audience
Designed for software developers, engineers, and computer scientists with basic Python skills, this course is ideal if you want to build practical recommendation engines. If you're eager to apply machine learning and AI to real-world problems and enhance user experiences, you'll find the content both accessible and rewarding.
