Pinned Repositories
18338
AI-System
System for AI Education Resource.
awesome-causality-algorithms
An index of algorithms for learning causality with data
awesome-chatgpt-prompts
This repo includes ChatGPT prompt curation to use ChatGPT better.
Awesome-explainable-AI
A collection of research materials on explainable AI/ML
awesome-reinforcement-learning-zh
中文整理的强化学习资料（Reinforcement Learning）
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
citeulike-a
Dataset citeulike-a for 'Collaborative Topic Regression with Social Regularization' (CTRSR)
collabtm
collaborative topic modeling
compas-analysis
Data and analysis for 'Machine Bias'
g-github-science's Repositories
g-github-science/Awesome-explainable-AI
A collection of research materials on explainable AI/ML
g-github-science/18338
g-github-science/AI-System
System for AI Education Resource.
g-github-science/awesome-causality-algorithms
An index of algorithms for learning causality with data
g-github-science/awesome-chatgpt-prompts
This repo includes ChatGPT prompt curation to use ChatGPT better.
g-github-science/awesome-reinforcement-learning-zh
中文整理的强化学习资料（Reinforcement Learning）
g-github-science/awesome-self-supervised-learning
A curated list of awesome self-supervised methods
g-github-science/cs229m_notes
g-github-science/ctpfrec
Python implementation of "Content-based recommendations with poisson factorization", with some extensions
g-github-science/d2l-en
Interactive deep learning book with code, math, and discussions. Available in multi-frameworks. Adopted at 140 universities.
g-github-science/d2l-pytorch-colab
Automatically Generated Notebooks for Colab
g-github-science/DETM
g-github-science/dlwpt-code
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
g-github-science/dragonnet
g-github-science/ETM
Topic Modeling in Embedding Spaces
g-github-science/hpc_jupyter_setup
run Jupyter servers on the HPC and connect to them
g-github-science/interpretable-machine-learning
g-github-science/introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
g-github-science/introRL
Intro to Reinforcement Learning (强化学习纲要）
g-github-science/learning-fair-representations
Python numba implementation of Zemel et al. 2013
g-github-science/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
g-github-science/nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
g-github-science/pmtk3
Probabilistic Modeling Toolkit for Matlab/Octave.
g-github-science/probabilistic-models
Collection of probabilistic models and inference algorithms
g-github-science/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
g-github-science/Spoon-Knife
This repo is for demonstration purposes only.
g-github-science/stochasticLDA
Python implementation of Stochastic Variational Inference for LDA
g-github-science/svinet
This package implements algorithms for identifying overlapping communities in large undirected networks. The sampling based algorithms derive from stochastic variational inference under the (assortative) mixed-membership stochastic blockmodel. For details see the following reference: http://www.pnas.org/content/early/2013/08/14/1221839110.full.pdf
g-github-science/topological-autoencoders
Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
g-github-science/varying-coefficient-net-with-functional-tr
[ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effects