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cuda

Using CUDA-accelerated Monte Carlo for option pricing. Developing a option pricing system in CUDA.

da-rnn

Dual-Stage Attention-Based Recurrent Neural Net for Time Series Prediction

da-rnn-1

📃 𝖀𝖓𝖔𝖋𝖋𝖎𝖈𝖎𝖆𝖑 PyTorch Implementation of DA-RNN (arXiv:1704.02971)

da-rnn-in-tensorflow-2-and-pytorch

A Tensorflow 2 (Keras) implementation of DA-RNN (A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction, arXiv:1704.02971)

danser-www-19

data-science-on-gcp

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

deep-convolution-stock-technical-analysis

Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.

deep-learning-for-order-book-price-and-movement-predictions

Limit Order Book data analysis and modeling using LSTM network

deep-learning-interview-book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deep-orderbook

Deep learning modelling of orderbooks

deep-stock

Deep Learning for Stock Market

deep-trading

Algorithmic trading with deep learning experiments

deep_trader

This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deeplob-deep-convolutional-neural-networks-for-limit-order-books

This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.

deeptables

DeepTables: Deep-learning Toolkit for Tabular data

deeptimeseriesmodel

A paper list for Time series modelling, including prediciton and anomaly detection

deltapy

DeltaPy - Tabular Data Augmentation (by @firmai)

devilyuan

DevilYuan股票量化系统

dl4stock

This is the project for deep learning in stock market prediction.

dtale

Visualizer for pandas data structures

dynamic-cnn-for-modelling-sentences

An implementation of the CNN model described in "A Convolutional Neural Network for Modelling Sentences". Kalchbrenner et al. 2014

dynamic-cnn-sentence-classification-tf

dynamic-graph-papers

动态图表示论文汇总

dynamic_convolutional_neural_network

implementation of dynamic convolutional neural network for text classification

dynamicgem

elegantrl

Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

explicitimpliedvolatility

For the first time we derived a closed form solution for Black-Scholes impled volatility