함께 코드 따라하기
코드 따라하기 ↗AI Python Zero-to-Hero: Build an AI Movie Night Recommendation Tool
Pieter Moors, a Senior Data Scientist at DataCamp, shows you how to build an AI-powered movie night recommendation tool.
Pieter Moors
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실습 문제하고 트랙하세요.
Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.관련
튜토리얼
Recommendation System for Streaming Platforms Tutorial
In this Python tutorial, explore movie data of popular streaming platforms and build a recommendation system.
튜토리얼
Beginner Tutorial: Recommender Systems in Python
Build your recommendation engine with the help of Python, from basic models to content-based and collaborative filtering recommender systems.

코딩 실습
Retrieval Augmented Generation with the OpenAI API & Pinecone
Build a movie recommender system using GPT and learn key techniques to minimize hallucinations and ensure factual answers.


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.