RAdam implemented in Keras & TensorFlow

optimizer & lr scheduler & loss function collections in PyTorch

基于tf.keras的多标签多分类模型

Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay

A collection of deep learning models (PyTorch implemtation)

Object detection and instance segmentation on MaskRCNN with torchvision, albumentations, tensorboard and cocoapi. Supports custom coco datasets with positive/negative samples.

Pytorch implementation of lookahead optimizer(https://arxiv.org/pdf/1907.08610.pdf) and RAdam(https://arxiv.org/pdf/1908.03265.pdf)

Nadir: Cutting-edge PyTorch optimizers for simplicity & composability! 🔥🚀💻

Literature survey of convex optimizers and optimisation methods for deep-learning; made especially for optimisation researchers with ❤️

On The Variance Of The Adaptive Learning Rate And Beyond in tensorflow

MXNet implementation of RAdam optimizer

tf-keras-implemented YOLOv2

Ranger - a synergistic optimizer using RAdam (Rectified Adam) and Lookahead in one codebase

Benchmarking Optimizers for Sign Language detection

Classify known sites from around the world, given challenging and very big data set. This project is based on a kaggle competition.

python code, notebooks and Images used for AI502 Midterm Project.