Python - 100天从新手到大师

Learn how to design, develop, deploy and iterate on production-grade ML applications.

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

Google Research

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.

Course Files for Complete Python 3 Bootcamp Course on Udemy

This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security,…

The fastai book, published as Jupyter Notebooks

Python programs, usually short, of considerable difficulty, to perfect particular skills.

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

A High-Quality Real Time Upscaler for Anime Video

Neural Networks: Zero to Hero

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

💿 Free software that works great, and also happens to be open-source Python.

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Companion webpage to the book "Mathematics For Machine Learning"

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

Official inference library for Mistral models

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Python toolkit for quantitative finance

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Sample code for Channel 9 Python for Beginners course

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Tutorials and programming exercises for learning Q# and quantum computing

Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

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

Bayesian optimization in PyTorch