This is the material for Jose Portilla's Spark and Python for Big Data and ML course.
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Updated
Aug 4, 2024 - Jupyter Notebook
This is the material for Jose Portilla's Spark and Python for Big Data and ML course.
Recommendation Systems course at AGH UST 2023/2024. This repository is packed with Jupyter Notebook files, written in Python, to guide you through the theory and implementation of recommendation algorithms.
The objective of this project is to build a recommendation system to recommend movies to users based on the ratings given to different movies by the users.
This repository contains code and analysis for a homework assignment on recommendation systems and clustering algorithms in Python. Implements techniques like minhash, LSH, feature engineering, dimensionality reduction, K-means and DBSCAN clustering.
A recommendation engine for the clever. Caidin is a Python library that empowers developers to build smart recommendation systems, including content-based and collaborative filtering methods, making personalized recommendations a breeze.
Various recommendation approaches on IBM Watson platform
Datasets and code used for Scientific Article Recommendations
A collection of team projects
This is the content of Jose Portilla's Udemy course on Scala and Spark for Big Data and Machine Learning.
The Movie Recommendation System is an advanced machine learning project developed in Python, aimed at providing tailored movie suggestions to users based on their preferences and viewing habits. Leveraging various machine learning algorithms and data processing techniques, this system offers a personalized and enriched movie-watching experience.
Django SDK for the Very Easy AI Recommendation engine
The repository prompts the user to select the recommendation approach, user-based (correlation). Based on the selected approach and similarity metric, this function predicts the rating for specified user and item and also suggests if the item could be recommended to the user.
Implementation of Data Mining Algorithm on Spark with Python3
Discover the Machine learning datasets! Diverse content for 🎓 education, 📊 research, 👥 non-profit use and experimenting. Download, merge files for 📝 convenience. Contribute to enhance language modeling, 🤖 machine learning, 🎓 education, data analysis, and 🧪 software development. Note: Content sourced for non-profit, educational use. Enjoy! ;)
Book recommender api written in flask framework
This repository comprises of the projects and assignments that i have completed during my tenure at Great Lakes for the course program PGP-AIML. This repository also includes the lab work thatwas done during the classes and even those that were given as assessments.
Collaborative filtering books recommender system
List of all ML projects
🟣 Recommendation Systems interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
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