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airbnb_recommendations

An Airbnb destination recommendation system (Kaggle competition) to predict a new user's booking destination given their demographics, web session records, and other summary statistics. Coded in Python.

asteroid

The PyTorch-based audio source separation toolkit for researchers || Pretrained models available

at-conv-lstm

A Hybrid Deep Learning Model with Attention based ConvLSTM Networks for Short-Term Traffic Flow Prediction

bert-bilstm-crf-ner

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

bert-use-demo

the demo for bert

bertviz

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

chineseholiday

API to Check whether a date is a chinese holiday **法定节假日API

cogan-tensorflow

Implement Coupled Generative Adversarial Networks in Tensorflow

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deeppavlov

An open source library for deep learning end-to-end dialog systems and chatbots.

deepst

Reconstruction of DeepST

denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

dual-path-rnns-dprnns-based-speech-separation

A PyTorch implementation of dual-path RNNs (DPRNNs) based speech separation described in "Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation".

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

graph_convolutional_lstm

Traffic Graph Convolutional Recurrent Neural Network

graphembeddingrecommendationsystem

Python based Graph Propagation algorithm, DeepWalk to evaluate and compare preference propagation algorithms in heterogeneous information networks from user item relation ship.

hatch

kaldi

This is the official location of the Kaldi project.

nlp-beginner

NLP上手教程

nlpbeginner

主要介绍了NLP的基础模型以及相关算法

oucml

pygcn

Graph Convolutional Networks in PyTorch

pytorch-kaldi

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

pytorch-qrnn

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

speech_recognition

Speech recognition module for Python, supporting several engines and APIs, online and offline.

svoice

We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.

tencent2018_lookalike_rank7th

The code for 2018 Tencent College Algorithm Contest, and the online result ranks 7th.

text-classification-cnn-rnn

CNN-RNN中文文本分类，基于TensorFlow