Tanishq-01's Stars
Asabeneh/30-Days-Of-React
30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
JaidedAI/EasyOCR
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
NielsRogge/Transformers-Tutorials
This repository contains demos I made with the Transformers library by HuggingFace.
microsoft/computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
hongleizhang/RSPapers
RSTutorials: A Curated List of Must-read Papers on Recommender System.
rguthrie3/DeepLearningForNLPInPytorch
An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
tsinghua-fib-lab/GNN-Recommender-Systems
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
towardsai/tutorials
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
AlphaJia/pytorch-faster-rcnn
pytorch based implementation faster rcnn
Yangyangii/GAN-Tutorial
Simple Implementation of many GAN models with PyTorch.
rn5l/session-rec
Python-based framework for building and evaluating session-based and session-aware recommender systems.
ahkarami/Great-Deep-Learning-Tutorials
A Great Collection of Deep Learning Tutorials and Repositories
piyushpathak03/Recommendation-systems
Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems
Jyonn/ONCE
(WSDM 2024) Official implementation of the paper "ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models"
taylorhawks/RNN-music-recommender
sequential content-based recommendation system
archd3sai/News-Articles-Recommendation
Objective of the project is to build a hybrid-filtering personalized news articles recommendation system which can suggest articles from popular news service providers based on reading history of twitter users who share similar interests (Collaborative filtering) and content similarity of the article and user’s tweets (Content-based filtering).
MathProgrammer/AtCoder
Xinyi6/E-commerce-recommendation-system
Recommender System； Collaborative Filtering；Content-Based Algorithm
Chandru-21/End-to-End-Movie-Recommendation-System-with-deployment-using-docker-and-kubernetes
Content Based Recommendation system uses attributes of the content to recommend similar content. It doesn't have a cold-start problem because it works through attributes or tags of the content, such as actors, genres or directors, so that new movies can be recommended right away.
MainakRepositor/Product-Recommendation-System
Product Recommendation System using collaborative based and content based filtering
chen0040/mxnet-recommender
Collaborative Filtering NN and CNN based recommender implemented with MXNet
pm390/recsys2022
Code repo of solution of 11th place in Recsys Challenge 2022
aliceagrawal/HM-Recommender-System-App
Built a collaborative filtering and content-based recommendation/recommender system specific to H&M using the Surprise library and cosine similarity to generate similarity and distance-based recommendations.
karenwky/Recommendation_System_Allrecipes
recommending recipes with content-based filtering approach
shavy4452/Clash-WhatsApp-Bot
A Clash Of Clans Bot based on a WhatsApp client library for NodeJS that connects through the WhatsApp Web Socket.
titericz/otto2023_giba
OTTO – Multi-Objective Recommender System
ika9810/Atcoder-Daily-Contests
✨Atcoder Contests✨ - You can get Today's Virtual Atcoder Contests Everyday
mansi-palekar/Spotify_Music_Recommendations
This repository contains the implementation and deployment of a content-based music recommendation system using Streamlit.
StivenMetaj/Recommender_Systems_Challenge_2020
Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi
bsinghpratap/machine-learning-flashcards
Machine learning flashcards