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21 Lessons, Get Started Building with Generative AI
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Examples and guides for using the OpenAI API
Python Data Science Handbook: full text in Jupyter Notebooks
12 Weeks, 24 Lessons, AI for All!
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
This is a repo with links to everything you'd ever want to learn about data engineering
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Anthropic's educational courses
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
Natural Language Processing Tutorial for Deep Learning Researchers
Your new Mentor for Data Science E-Learning.
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.
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! W…
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Public facing notes page
YSDA course in Natural Language Processing
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Automatic extraction of relevant features from time series:
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
An annotated implementation of the Transformer paper.
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai