jyotipmahes / ML-Interview-Prep
A Jupyter notebook collection of from-scratch ML algorithm implementations and interview prep for machine learning engineer roles.
jyotipmahes / ML-Interview-Prep
karpathy / nn-zero-to-hero
Neural Networks: Zero to Hero
skilltraining-project / skill-training
Skill training with a corruption and reconstruction loop: train an agent's skill library, not its weights.
mrdbourke / zero-to-mastery-ml
All course materials for the Zero to Mastery Machine Learning and Data Science course.
roboflow / supervision
We write your reusable computer vision tools. 💜
stefan-jansen / machine-learning-for-trading
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
rednote-machine-learning / RedKnot
Efficient Long-Context LLM Serving with Head-Aware KV Reuse and SegPagedAttention
mrdbourke / pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
openvinotoolkit / openvino
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
pyannote / pyannote-audio
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
facebookresearch / sam2
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
ageron / handson-ml3
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.
fastai / fastbook
The fastai book, published as Jupyter Notebooks
twitter / the-algorithm
Source code for the X Recommendation Algorithm
greyhatguy007 / Machine-Learning-Specialization-Coursera
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
facebookresearch / segment-anything
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.
udlbook / udlbook
Understanding Deep Learning - Simon J.D. Prince
ageron / handson-mlp
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, PyTorch, and Hugging Face libraries.
datawhalechina / llm-algo-leetcode
LLM algorithm practice lab with theory, solutions, and test cases.《大模型算法与系统教程》面向大模型入门到进阶的算法实战教程，覆盖原理讲解、答案解析、测试用例与 CUDA/Triton 实战。
openvinotoolkit / openvino_notebooks
📚 Jupyter notebook tutorials for OpenVINO™