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100-days-of-ml-code

100 Days of ML Coding

ai-expert-roadmap

Roadmap to becoming an Artificial Intelligence Expert in 2022

amazon-sagemaker-mlops-workshop

Machine Learning Ops Workshop with SageMaker: lab guides and materials.

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

awesome

😎 Awesome lists about all kinds of interesting topics

awesome-jupyterlab

A curated list of awesome JupyterLab extensions and resources

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

black

The uncompromising Python code formatter

boost-python-examples

Some examples for the use of boost::python

browser-ml-inference

Edge Inference in Browser with Transformer NLP model

codon

A high-performance, zero-overhead, extensible Python compiler using LLVM

colossalai

Making big AI models cheaper, easier, and more scalable

cookbook

The Data Engineering Cookbook

course

The Hugging Face course

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

data-engineering-zoomcamp

Free Data Engineering course!

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

diagrams

:art: Diagram as Code for prototyping cloud system architectures

dl_enso

CNN for climate forecast

dowhy

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.

easyocr

Ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

face_eyes_detector

fastai_model_deploy

fastchat

The release repo for "Vicuna: An Open Chatbot Impressing GPT-4"

from-0-to-research-scientist-resources-guide

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

gan

Tooling for GANs in TensorFlow