Data Scenario #8 - Recommendation System with NMF in Python : Book Recommendation Project скачать в хорошем качестве

Data Scenario #8 - Recommendation System with NMF in Python : Book Recommendation Project

🚀 🤖 This entire video was generated by an AI agent. Visit us at https://orange-brackets.com/ to turn your notebooks into courses! ------------------------------------------------------------ 📚 In this hands-on data science project, you’ll learn how to build a personalized book recommendation system using Non-negative Matrix Factorization (NMF) in Python. You've just joined BookHive — an online bookstore looking to level up its recommendation engine. Using only user-book rating data, we'll walk through how to uncover hidden preferences and make personalized suggestions for every reader. 🔧 What You’ll Learn: How recommendation systems work (collaborative filtering) How to use NMF for dimensionality reduction Creating and transforming a user-item matrix Predicting missing ratings using matrix factorization Evaluating model accuracy with RMSE Tuning model performance by adjusting number of latent features 💻 Get the Code & Notebook Follow along with the full notebook and all the project files here: 👉 GitHub Repository: https://github.com/ahmadvh/Data-Scenario 🛠 Tools & Libraries: Python (pandas, numpy, matplotlib) scikit-learn 🧠 Perfect For: Data science beginners Aspiring machine learning engineers Anyone looking to add real-world projects to their portfolio 📌 Don’t forget to like, subscribe, and check out the full Data Scenarios playlist:    • Data Scenarios