Deep Learning For Recommendation Systems
robi56
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
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Results: 27
robi56
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
TheAlgorithms
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
TheAlgorithms
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
ahmedfgad
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
DerwenAI
Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
lightgbm-org
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and…
DLR-RM
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
eriklindernoren
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from li…
vwxyzjn
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
uber
Uplift modeling and causal inference with machine learning algorithms
py-why
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic de…
Nixtla
Scalable and user friendly neural :brain: forecasting algorithms.
PennyLaneAI
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from…
Trusted-AI
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Owner-curated external sources. Not filtered by the scores or compatibility controls above; excluded from GitHub rankings and automatic installation.
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