Stars
🤗 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.
Models and examples built with TensorFlow
scikit-learn: machine learning in Python
A toolkit for developing and comparing reinforcement learning algorithms.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
The interactive graphing library for Python ✨
Datasets, Transforms and Models specific to Computer Vision
Image augmentation for machine learning experiments.
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Anomaly detection related books, papers, videos, and toolboxes
A Python implementation of global optimization with gaussian processes.
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Distributed Asynchronous Hyperparameter Optimization in Python
Keras code and weights files for popular deep learning models.
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Image augmentation library in Python for machine learning.
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-contrib-python-headless packages.
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Manipulation and analysis of geometric objects
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"
Read, modify and write DICOM files with python code
A lightweight library for PyTorch training tools and utilities
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons