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going-deeper-with-convolutional-neural-network-for-stock-market-prediction

Repository for Going Deeper with Convolutional Neural Network for Stock Market Prediction

hydra

Hydra is a free tool for predicting stock prices using technical analysis

hyperas

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

keras-attention-mechanism

Attention mechanism Implementation for Keras.

keras-gat

Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)

keras-just-another-network-janet

Keras implementation of [The unreasonable effectiveness of the forget gate](https://arxiv.org/abs/1804.04849)

keras-padam

Keras implementation of Padam from "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks"

keras-stochastic-weight-averaging

Keras callback function for stochastic weight averaging

keras-tcn

Keras Temporal Convolutional Network.

keras-visualize-activations

Activation Maps Visualization for Keras.

keras2-wavenet

A Keras2-Version of Google's WaveNet

kerasdropconnect

An implementation of DropConnect Layer in Keras

lectures

Oxford Deep NLP 2017 course

lstm---stock-prediction

A long term short term memory recurrent neural network to predict stock data time series

lstm_attention

attention-based LSTM/Dense implemented by Keras

lstm_attention_stock

lstmcell

Implement modern LSTM cell by tensorflow and test them by language modeling task for PTB. Highway State Gating, Hypernets, Recurrent Highway, Attention, Layer norm, Recurrent dropout, Variational dropout.

ml-stock-prediction

A toolset for stock prediction using reinforced learning, including a custom OpenAI environment.

mlstm-fcn

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

multi-factor-gm-wind-joinquant

基于掘金+万得+聚宽的多因子策略开发框架

nested-lstm

Keras implementation of Nested LSTMs

neural-networks-for-time-series-analysis

Compare how ANNs, RNNs, LSTMs, and LSTMs with attention perform on time-series analysis

new-york-stock-exchange-predictions-rnn-lstm

BEST SCORE ON KAGGLE SO FAR. Mean Square Error after repeated tuning 0.00032. Used stacked GRU + LSTM layers with optimized architecture, learning rate and batch size for best model performance. The graphs are self explanatory once you click and go inside !!!

nlp-stock-prediction

nlstm

Nested LSTM Cell

nn_playground

Experimental keras implementation of novel neural network structures

personae

📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.

portfolioopt

Financial Portfolio Optimization Routines in Python

predictingclosingpricetomorrow

Predict the change in closing price from one trading day to the next into one of four bands for any stock using technical indicators and financial ratios as features.