Hybrid movie recommendation web app using Machine Learning, the movie DB API, and Flask.
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Updated
May 22, 2023 - Jupyter Notebook
Hybrid movie recommendation web app using Machine Learning, the movie DB API, and Flask.
Different machine learning methods are used in this repository. It contains more than one sample notebook for these methods.
Sincere, a less biased hybrid movie recommendation system based on ratings.
This project implements a robust recommender system for book recommendations, leveraging ensemble methods, user-specific strategies, XGBoost, and extensive data preprocessing to achieve high performance in the Recommender System 2023 Challenge hosted by Kaggle for students of Politecnico di Milano's Recommender Systems course.
Curso Machine Learning por la Universidad de Stanford, a través de la plataforma Coursera. Este repositorio contiene todos los ejercicios resueltos. https://www.coursera.org/learn/machine-learning
基于 PaddlePaddle 框架复现 DLRM CTR 预估算法
A python project to extract Association Rules from IranITJobs2021 dataset using Apriori algorithm.
Sustainable Recipes. A Food Recipe Sourcing and Recommendation System to Minimize Food Miles
Wedding Package Recomendation API
Anime Recomender System
Product recommendation application, implemented with Angular 6, with demo in:
A system to recommend wines based on their description.
Leveraging Neo4j for recommending Job
Sistema de recomendación para la compra de un producto electrónico, incorpora resultados de búsqueda de Amazon, Ebay, Linio, OLX, Mercado Libre Colombia, Dondo, Exito.com y Falabella.
Execução Scripts do Livro Mastering Machine Learning Packt
Projects developed under the Data Mining II college chair during the 2019/2020 school year
Media player written in python and a small recommendation service
My kaggle Notebooks
Movie Recommender API: FastAPI-based backend for movie recommendations using collaborative filtering.
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