Popular GitHub Repositories for Probability Propagation

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Probabilistic language based on pattern matching and constraint propagation, 153 examples

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2025 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.

The basic distribution probability Tutorial for Deep Learning Researchers

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

仅使用numpy从头开始实现神经网络,包括反向传播公式推导过程; numpy构建全连接层、卷积层、池化层、Flatten层；以及图像分类案例及精调网络案例等,持续更新中... ...

Lecture notes on Bayesian deep learning

[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion. Semi-supervised VOS as well!

collections of data science, machine learning and data visualization projects with pandas, sklearn, matplotlib, tensorflow2, Keras, various ML algorithms like random forest classifier, boosting, etc

List of DL topics and resources essential for cracking interviews

Minimal and clean examples of machine learning algorithms implemented in Julia

Normalizing flows in PyTorch

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

Rethinking Knowledge Graph Propagation for Zero-Shot Learning, in CVPR 2019