recommendation-engine

Music Recommender System

Apache Zeppelin notebooks for Recommendation Engines using Keras and Machine Learning on Apache Spark

BookCrossing data cleansing and book Recommendations

Machine Learning IPython Notebooks

This repo contains jupyter notebook file for my blog about Spotify Recommendation Engine in Section.IO

Building a Netflix Recommendation Engine using Python in Google Colab or Jupyter Notebook.

My project on analyzing the movie data set, and creating a recommendation engine using that analysis.

A python movie recommendation system created on jupyter notebook.

Data Science Project for Udacity's Data Scientist Program. Using Python in Jupyter Notebook.

In the IBM Watson Studio, there is a large collaborative community ecosystem of articles, datasets, notebooks, and other A.I. and ML. assets. Users of the system interact with all of this. This is a recommendation system project to enhance the user experience and connect them with assets. This personalizes the experience for each user.

In this notebooks a baseline Movie Recommendation System is being build using TMDB 5000 Movie Dataset.

Web-app and jupyter notebook, fully documented for Capstone of Udacity data science ND. Uses FunkSVD/handwritten gradient descent algorithm plus chi sq to determine recommendations for users based on demographic

Built a Job Recommendation System that matches candidates to jobs based on their skills. Applied TF-IDF Vectorization and Cosine Similarity to recommend the top N relevant jobs. Implemented in Python (Pandas, NumPy, Scikit-learn) with a clean Jupyter Notebook workflow.

A machine learning–based recommendation system that suggests relevant items using data-driven techniques such as similarity measures and collaborative filtering. The project demonstrates end-to-end workflow including data preprocessing, feature engineering, model building, and evaluation in a notebook-driven pipeline.