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polyaxon

A platform that helps you build, manage and monitor deep learning models

practical-pytorch

PyTorch tutorials demonstrating modern techniques with readable code

practical_nlp_in_pytorch

A repository containing tutorials for practical NLP using PyTorch

python-ffm

Python Wrapped LibFFM [bigdata数据]

python-libffm

A Python wrapper for the libffm library. [ bigdata.tr.txt]

pytorch-dnc

Differentiable Neural Computers, for Pytorch

pytorch-ntm

Neural Turing Machines (NTM) - PyTorch Implementation

pytorch-pretrained-bert

The Big-&-Extending-Repository-of-Transformers: PyTorch pretrained models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.

pytorch-qrnn

PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM

pytorch-softdtw-cuda

Fast CUDA implementation of (differentiable) soft dynamic time warping for PyTorch using Numba

pytorchic-bert

Pytorch Implementation of Google BERT

pytorchluongattention

rcm-question-answering

recurrent-transformer

[ACL 2020] PyTorch code for MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning

reformer-pytorch

Reformer, the efficient Transformer, in Pytorch

roberta_zh

RoBERTa中文预训练模型: RoBERTa for Chinese

roformer_pytorch

RoFormer_pytorch

rossmann-kaggle

segatron_aaai

codes and pre-trained models of paper "Segatron: Segment-aware Transformer for Language Modeling and Understanding"

seq2seq

基于Pytorch的中文聊天机器人 集成BeamSearch算法

seq2seq.pytorch

Sequence-to-Sequence learning using PyTorch

sha-rnn

Single Headed Attention RNN - "Stop thinking with your head"

soft-dtw

Python implementation of soft-DTW.

sru

Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)

stockpredictionai

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 Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

stockpredictionrnn

High Frequency Trading Price Prediction using LSTM Recursive Neural Networks

stocks_rnn

Stock price prediction with LSTMs in TensorFlow

supply-demand-forecasting

supply demmand gap prediction for ride-hailing

tensorflow

forked from YJango 2017-06-05

tensorflow-tutorials-for-time-series

TensorFlow Tutorial for Time Series Prediction