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adabelief-optimizer

Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

adabound

An optimizer that trains as fast as Adam and as good as SGD.

adahessian

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

adamw-and-sgdw

Decoupled Weight Decay Regularization (ICLR 2019)

algorithmic-efficiency

MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome-ai-in-finance

🔬 A curated list of awesome machine learning strategies & tools in financial market.

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

awesome-meta-learning

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

curveball-pytorch

An Implementation of "Small steps and giant leaps: Minimal Newton solvers for Deep Learning" In pytorch

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

digiface1m

gradient_descent_viz

interactive visualization of 5 popular gradient descent methods with step-by-step illustration and hyperparameter tuning UI

machine-learning-surveys

A curated list of Machine Learning Surveys, Tutorials and Books.

maml-pytorch

A Pytorch implementation of MAML

neural-em

Code for the "Neural Expectation Maximization" paper.

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

omniglot

Omniglot data set for one-shot learning

pyhessian

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

pytorch-cifar

95.47% on CIFAR10 with PyTorch

pytorch-hessian-eigenthings

Efficient PyTorch Hessian eigendecomposition tools!

pytorch-optimizer

torch-optimizer -- collection of optimizers for Pytorch

pytorch_optimizer

optimizer & lr scheduler & loss function collections in PyTorch

quandl-python

quantresearch

Quantitative analysis, strategies and backtests

saddlefreeoptimizer

A second order optimizer for TensorFlow that uses the Saddle-Free method.

seaborn-data

Data repository for seaborn examples

sophia

The official implementation of “Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training”

transformer-xl