ManasRahman

ManasRahman's Stars

• ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

  500 AI Machine learning Deep learning Computer vision NLP Projects with code

  21.3k607595.3k

• RUCAIBox/RecBole

  A unified, comprehensive and efficient recommendation library

  Language:Python3.5k42996621

• RUCAIBox/Awesome-RSPapers

  Recommender System Papers

  950315145

• RUCAIBox/RecSysDatasets

  This is a repository of public data sources for Recommender Systems (RS).

  Language:Python8921439133

• RUCAIBox/RecBole2.0

  An up-to-date, comprehensive and flexible recommendation library

  18810423

• 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

  Language:Jupyter Notebook1787248

• hyp1231/AmazonReviews2023

  Scripts for processing the Amazon Reviews 2023 dataset; implementations and checkpoints of BLaIR: "Bridging Language and Items for Retrieval and Recommendation".

  Language:Python14832128

• RUCAIBox/RecBole-CDR

  This is a library built upon RecBole for cross-domain recommendation algorithms

  Language:Python9263713

• nijianmo/recsys_justification

  Language:Python622810

• Blockchain-for-Developers/merkle-tree

  Merkle Tree Implementation for Lab07

  Language:Python453056

• FarzadNekouee/Retail_Customer_Segmentation_Recommendation_System

  Analyzing and transforming a UK-based retail dataset (2010-2011) into a customer-centric format for customer segmentation using K-means clustering. Implementing a personalized recommendation system to enhance marketing strategies and boost sales.

  Language:Jupyter Notebook36102

• AaronHeee/FDU-Recommender-Systems-for-Douban-Movie

  Douban Movies Recommendation based on NeuralFM with Tensorflow. This is a project in Social Network Analysis@FDU.

  Language:HTML29012

• l3lackcurtains/github-reviewer-recommender

  :dolphin: Reviewer recommendation system for Pull Requests in github using social network analysis and topic modeling.

  Language:Jupyter Notebook11202

• fatihsen20/Frequent-Mining-Algorithms

  "Frequent Mining Algorithms" is a Python library that includes frequent mining algorithms. This library contains popular algorithms used to discover frequent items and patterns in datasets. Frequent mining is widely used in various applications to uncover significant insights, such as market basket analysis, network traffic analysis, etc.

  Language:Python10200

• VanessaSingh/Comparison-of-Association-Rule-Mining-Algos

  Comparison of Apriori, FP- Growth and ECLAT

  Language:Jupyter Notebook9202

• aryabarzan/negFINpy

  The python implementation of negFIN Algorithm (a fast algorithm for Frequent Itemset Mining)

  Language:Python400

• bashnick/arules_shared

  developing an eclat library for python

  Language:Jupyter Notebook4104

• Hellisotherpeople/ECLAT-Association-Rule-Mining

  An implementation of the Equivalence Class Transformation Association Rule Mining algorithim in Python

  Language:Jupyter Notebook4401

• RoobiyaKhan/Association-Rule-Mining-in-R-and-Python

  Apriori and Eclat

  Language:Python4109

• aryabarzan/NEclatClosed

  This is a vertical algorithm for mining frequent closed itemsets.

  Language:Java300

• asoulet/ResPat

  Reservoir Pattern Sampling in Data Streams

  Language:Java2101

• BurraAbhishek/Python_Hadoop_MapReduce_MarketBasketAnalysis

  Market Basket Analysis using Hadoop MapReduce in Python

  Language:Python2102

• ranriy/Frequent-Itemset-Mining-using-Hadoop

  Implementation of the Apriori algorithm using Mapper and Reducer programs in Python through Hadoop streaming

  Language:Python2211

• SaiPavan93-zz/SVM-and-ECLAT-implementation

  Implementation of SVM and ECLAT on Congressional Dataset

  Language:Python2102

• 3sannasia/Infinithought

  Movie Recommendation System using Social Networks

  Language:Python1100

• aryabarzan/dFIN

  The implementation of dFIN algorithm, “Zhi-Hong Deng. DiffNodesets: An efficient structure for fast mining frequent itemsets. Applied Soft Computing, 41: 214-223, 2016”.

  Language:C++100

• aryabarzan/negFIN

  The implementation of negFIN algorithm.

  Language:C++1012

• mghorbani2357/TT-Miner-Topology-Transaction-Miner-for-Mining-Closed-Itemset

  Language:Python1100

• RUCAIBox/Ada2Fair

  The official implementation code of the RecSys 2024 short paper "Promoting Two-sided Fairness with Adaptive Weights for Providers and Customers in Recommendation".

  Language:Python100

• ShashankRV1/Community-Recommendation-in-Social-Networks

  An Efficient and Improved Algorithm for a Recommender System to Detect & Recognize Communities in Social Networks. Using Python.

  Language:Python110