peterleong's Stars
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
shap/shap
A game theoretic approach to explain the output of any machine learning model.
Hannibal046/Awesome-LLM
Awesome-LLM: a curated list of Large Language Model
janishar/mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
tebelorg/RPA-Python
Python package for doing RPA
javascriptdata/danfojs
Danfo.js is an open source, JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.
alpa-projects/alpa
Training and serving large-scale neural networks with auto parallelization.
Trusted-AI/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.
quantopian/research_public
Quantitative research and educational materials
ageron/tf2_course
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
hexiangnan/neural_collaborative_filtering
Neural Collaborative Filtering
mpezeshki/pytorch_forward_forward
Implementation of Hinton's forward-forward (FF) algorithm - an alternative to back-propagation
kengz/SLM-Lab
Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
aharley/nn_vis
An interactive visualization of neural networks
microsoft/PyCodeGPT
A pre-trained GPT model for Python code completion and generation
amueller/ml-training-intro
Materials for the "Introduction to Machine Learning" class
FrancescaLazzeri/Machine-Learning-for-Time-Series-Forecasting
kozyrkov/deep-learning-walkthrough
Slides showing a walkthrough of the tutorial by kozyrkov and bkungfoo available at github.com/google-aai/sc17.
DavidLandup0/dl4cv
Series of notebooks accompanying the book "Practical Deep Learning for Computer Vision with Python" to get you from walking to running in CV with Keras/TensorFlow, KerasCV and PyTorch
kozyrkov/deep-learning-tutorial
SuperComputing 2017 Deep Learning Tutorial
mas-veritas2/veritastool
Veritas Diagnosis Toolkit for Fairness Assessment
rasbt/PyMLSlides
Slides for my machine learning course based on Sebastian Raschka's Python Machine Learning book
jeongyoonlee/av-for-concept-drift-in-automl
Code for Adversarial Validation Approach to Concept Drift Problem in Automated Machine Learning Systems
Bluelord/ML_Cookbook
Notebook of practice code and notes for Python ML Cookbook
mrvee-qC-bee/SCA2023_Workshop
Qiskit Workshop repository for Future of High Performance Computing with Quantum at SCA 2023
peterleong/aistart2021
peterleong/aistart2022
AI Jump-start 2022
peterleong/handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
peterleong/stat453-deep-learning-ss21
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)
quekyuchern/Movie-Rating-Prediction