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📚 Freely available programming books
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
All Algorithms implemented in Python
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
FastAPI framework, high performance, easy to learn, fast to code, ready for production
The world's simplest facial recognition api for Python and the command line
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
A paper list of object detection using deep learning.
An educational resource to help anyone learn deep reinforcement learning.
Style transfer, deep learning, feature transform
TensorFlow CNN for fast style transfer ⚡🖥🎨🖼
Python bindings for FFmpeg - with complex filtering support
An open-source post-exploitation framework for students, researchers and developers.
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Bandit is a tool designed to find common security issues in Python code.
Trio – a friendly Python library for async concurrency and I/O
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …
Extract Keywords from sentence or Replace keywords in sentences.
Most popular metrics used to evaluate object detection algorithms.