Popular GitHub Repositories for Bayesian Personalized Ranking

A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Machine learning, in numpy

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

? Scalable embedding, reasoning, ranking for images and sentences with CLIP

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

Bayesian Modeling and Probabilistic Programming in Python

Deep universal probabilistic programming with Python and PyTorch

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Automated Machine Learning with scikit-learn

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Torchreid: Deep learning person re-identification in PyTorch.

Probabilistic reasoning and statistical analysis in TensorFlow

An open source AI wearable device that captures what you say and hear in the real world and then transcribes and stores it on your own server. You can then chat with Adeus using the app, and it will have all the right context about what you want to talk about - a truly personalized, personal AI.

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

Learning to Rank in TensorFlow

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.