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Starred repositories
🦜🔗 Build context-aware reasoning applications
Examples and guides for using the OpenAI API
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
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 ;)
A game theoretic approach to explain the output of any machine learning model.
The fastai book, published as Jupyter Notebooks
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
A guidance language for controlling large language models.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Instruct-tune LLaMA on consumer hardware
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…
Data and code behind the articles and graphics at FiveThirtyEight
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
The "Python Machine Learning (1st edition)" book code repository and info resource
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
QLoRA: Efficient Finetuning of Quantized LLMs
Public facing notes page
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
A collection of pre-trained, state-of-the-art models in the ONNX format
Automatic extraction of relevant features from time series:
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding