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Starred repositories
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.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Python programs, usually short, of considerable difficulty, to perfect particular skills.
The fastai book, published as Jupyter Notebooks
Learn OpenCV : C++ and Python Examples
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
This repository is primarily maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), ar…
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
This repository contains implementations and illustrative code to accompany DeepMind publications
A multi-voice TTS system trained with an emphasis on quality
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 th…
A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.
Public facing notes page
🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
PyTorch code and models for the DINOv2 self-supervised learning method.
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
A collection of pre-trained, state-of-the-art models in the ONNX format
Efficient Image Captioning code in Torch, runs on GPU
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
Create delightful software with Jupyter Notebooks
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Text recognition (optical character recognition) with deep learning methods, ICCV 2019
A small package to create visualizations of PyTorch execution graphs
Learn how to design, develop, deploy and iterate on production-grade ML applications.
A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.
The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python