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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.
Python Data Science Handbook: full text in Jupyter Notebooks
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
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.
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 ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
A game theoretic approach to explain the output of any machine learning model.
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Instruct-tune LLaMA on consumer hardware
A High-Quality Real Time Upscaler for Anime Video
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…
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Your new Mentor for Data Science E-Learning.
This repository contains implementations and illustrative code to accompany DeepMind publications
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Companion webpage to the book "Mathematics For Machine Learning"
PRML algorithms implemented in Python
High-Resolution Image Synthesis with Latent Diffusion Models
《李宏毅深度学习教程》(李宏毅老师推荐👍),PDF下载地址:https://github.com/datawhalechina/leedl-tutorial/releases
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Best Practices, code samples, and documentation for Computer Vision.
An open source implementation of CLIP.
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/