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2012-01_stanford_cs228

Probabilistic Graphical Models

advanced-swc

Intermediate and Advanced Software Carpentry tutorial material

advanced_programming_2021

aesara

Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.

aif360

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.

aitemplate

AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.

aix360

Interpretability and explainability of data and machine learning models

alphatensor

annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

ap_exam_2021

bayesian-modelling-in-python

A python tutorial on bayesian modeling techniques (PyMC3)

bayesianrnn

Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.

bnlearn

:exclamation: This is a read-only mirror of the CRAN R package repository. bnlearn — Bayesian Network Structure Learning, Parameter Learning and Inference. Homepage: https://www.bnlearn.com/

bnlearn-1

Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

cam

:exclamation: This is a read-only mirror of the CRAN R package repository. CAM — Causal Additive Model (CAM)

causal-learn

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

causaldiscoverytoolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

causalinferencecourse

Causal Inference Course Repository

causality-course-ethz

Code used in the causality course (401-4632-15) at ETH Zurich.

causalnex

A Python library that helps data scientists to infer causation rather than observing correlation.

cdmir

Causal Discovering, ModelIng and Reasoning

climate-dl

cobaya

Code for Bayesian Analysis

collab_project

comparecausalnetworks

A unified interface for the estimation of causal networks

computationalphysics

Introductory course in Computational Physics, including linear algebra, eigenvalue problems, differential equations, Monte Carlo methods and more.

computationalphysics2

Advanced course in Computational Physics, see texbook at http://compphysics.github.io/ComputationalPhysics2/doc/LectureNotes/_build/html/ with an emphasis on computational quantum mechanics, machine learning and quantum computing.

course-content-dl

NMA deep learning course

course-nlp

A Code-First Introduction to NLP course

course-v3

The 3rd edition of course.fast.ai