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Look inside
In this liveProject, you’ll take on the role of a machine learning engineer at CineMatch, a streaming service where frustrated users are abandoning the platform because they can’t find what to watch. Your mission: build an AI-driven recommendation engine for CineMatch’s shows! You’ll use Python, pandas, NumPy, and scikit-learn to build a hybrid engine that matches users to similar viewers via the K-Nearest Neighbors algorithm, and also boosts engagement with a predictive typing interface. You’ll monitor performance metrics like precision, recall, and F1-score to evaluate results, optimize your system to scale with large datasets, and visualize key insights with Matplotlib. By the end, you’ll have created a fast, smart recommendation engine that rivals those used by today’s top streaming platforms.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
prerequisites
This liveProject is for intermediate Python programmers who are comfortable working with structured data and want to build practical machine learning systems from scratch.
TOOLS
- Intermediate Python
- Intermediate pandas/scikit-learn
- Basic Matplotlib
- Basic Jupyter Notebook or IDE
TECHNIQUES
- Data wrangling
- Collaborative filtering
- Evaluation metrics
- Text processing
features
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A Movie Recommendation System with KNN & Predictive Text project for free
A Movie Recommendation System with KNN & Predictive Text project for free
team
monthly
annual
$49.99
$499.99
only $41.67 per month
- five seats for your team
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
- renews monthly, pause or cancel renewal anytime
- renews annually, pause or cancel renewal anytime
-
![]()
A Movie Recommendation System with KNN & Predictive Text project for free
