Stars
The author's officially unofficial PyTorch BigGAN implementation.
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Advers…
BERT as language model, fork from https://github.com/google-research/bert
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Transformer seq2seq model, program that can build a language translator from parallel corpus
An annotated implementation of the Transformer paper.
PyTorch Tutorial for Deep Learning Researchers
Statistical Inference and Sure Independence Screening via Ball Statistics
scikit-learn: machine learning in Python
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
LaTeX for personal resume, available as a template for use
Bayesian optimization in PyTorch
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
🤗 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.
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
A complete pytorch implementation of skip-gram
LaTeX style for Python highlighting
A Python implementation of global optimization with gaussian processes.
TensorFlow code and pre-trained models for BERT
The py version of toflow → https://github.com/anchen1011/toflow
A toolkit for developing and comparing reinforcement learning algorithms.