AI Python Zero-to-Hero: Build an AI Movie Night Recommendation Tool
Key Takeaways:- Learn how recommendation engines work and the techniques used to build them.
- Discover how to use AI to generate scikit-learn Python code for movie recommendations.
- Explore ways to leverage AI and Python to build practical tools for yourself.
Description
Recommendation engines are at the heart of personalized user experiences, and building one for movie recommendations is a great way to learn the underlying data science and machine learning techniques. By combining these techniques with AI-assisted coding tools, you can streamline the development process and create practical, personalized tools that are both fun and functional.
In this second session of our AI Python Zero-to-Hero code-along series, Pieter Moors, a Senior Data Scientist at DataCamp, will show you how to build an AI-powered movie night recommendation tool. You’ll learn how recommendation engines work, explore the data science and machine learning techniques behind them, and use AI to generate scikit-learn Python code for making movie recommendations. This session is perfect for data scientists and machine learning scientists looking to apply their skills to build creative and useful tools.
Presenter Bio
Pieter is a Data Scientist at DataCamp, where he focuses on driving innovation and ensuring the psychometric quality of skill assessments. He has a background in experimental psychology and visual perception and holds a Ph.D. in psychology from KU Leuven. In his free time, you can find him enjoying a nice craft beer after a good run.