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400_stocks_data_part2

400_stocks_data_zips

attentioned-dual-stage-stock-prediction

By PyTorch

capsnet

A pytorch implementation of Capsule Network.

cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

code

各个经典深度学习模型与经典数据集的搭配实战

daily-stock-data-set

Daily stock data set, including 000001, 000004, 399011, 600601 and 600615 from China Stock Market. All data is collected and preproccessed by Dingming Wu, ICRC, Harbin Institute of Technology, Shenzhen.

diebold-mariano-test

This Python function dm_test implements the Diebold-Mariano Test (1995) to statistically test forecast accuracy equivalence for 2 sets of predictions with modification suggested by Harvey et. al (1997).

jointly-modeling-transfer-learning-of-industrial-chain-information-and-deep-learning-for-stock-predi

the ralated files of Jointly modeling transfer learning of industrial chain information and deep learning for stock prediction

lime

Lime: Explaining the predictions of any machine learning classifier

ml_practice

ML Records in 1110 Lab of BUPT. Some detailed information can be referenced on: https://mathpretty.com/10388.html

python-elm

Extreme Learning Machine implementation in Python

pytorch-attention

pytorch neural network attention mechanism

pytorch-batch-attention-seq2seq

PyTorch implementation of batched bi-RNN encoder and attention-decoder.

pytorch-tutorial

Build your neural network easy and fast

pywt

PyWavelets - Wavelet Transforms in Python

qtf

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

representation-learning

Unsupervised Deep Learning and Representation Learning Tutorial

rnn-tutorial-gru-lstm

Language Model GRU with Python and Theano

sw_index_data

tcn

Sequence modeling benchmarks and temporal convolutional networks

transferlearning

Everything about Transfer Learning and Domain Adaptation--迁移学习

transformer

Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.