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🦜🔗 Build context-aware reasoning applications 🦜🔗
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
A simple screen parsing tool towards pure vision based GUI agent
A guidance language for controlling large language models.
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Instruct-tune LLaMA on consumer hardware
A collection of various deep learning architectures, models, and tips
Anthropic's educational courses
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
StableLM: Stability AI Language Models
PyTorch code and models for the DINOv2 self-supervised learning method.
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
LAVIS - A One-stop Library for Language-Vision Intelligence
QLoRA: Efficient Finetuning of Quantized LLMs
MiniCPM4 & MiniCPM4.1: Ultra-Efficient LLMs on End Devices, achieving 3+ generation speedup on reasoning tasks
Lab Materials for MIT 6.S191: Introduction to Deep Learning
A series of large language models trained from scratch by developers @01-ai
AirLLM 70B inference with single 4GB GPU
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
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!
A Bulletproof Way to Generate Structured JSON from Language Models
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
Democratizing Reinforcement Learning for LLMs