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ae_ts

Auto encoder for time series

arctic

High performance datastore for time series and tick data

arxivtimes

repository to research & share the machine learning articles

awesome-deep-learning-resources

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully.

cnn_tsc

A CNN for time-series classification

cryptocurrencytrader

A machine learning program in python to generate cryptocurrency trading strategies using machine and deep learning on price, hash rate and scraped forum sentiment data (using natural language processing). Sklearn and Tensorflow.

deep-reinforcement-learning-in-stock-trading

Using deep actor-critic model to learn best strategies in pair trading

deepnude-an-image-to-image-technology

DeepNude's pix2pixHD algorithms(proposed by NVIDIA) and general-purpose Image-to-Image theory and practice research. DeepNude的pix2pixHD算法（英伟达提出）以及通用的Image-to-Image理论与实践研究。

deepnude_nowatermark_withmodel

DeepNude源码，去水印，带三个模型文件下载地址 (cm.lib, mm.lib, mn.lib)，附使用说明，离线运行，下载即跑，基于GAN的一行命令给小姐姐"换"衣服。

fundamentals-of-deep-learning-book

Code companion to the O'Reilly "Fundamentals of Deep Learning" book

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hierarchical-attention-networks

Document classification with Hierarchical Attention Networks in TensorFlow

kaggle

kaggle-regression

A compiled list of kaggle competitions and their winning solutions for regression problems.

kaggle-web-traffic

1st place solution

kaggle-web-traffic-time-series-forecasting

won gold medal, 11th of 1095

keras-resnet

Residual networks implementation using Keras-1.0 functional API

lstm-human-activity-recognition

Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

lstm_tsc

An LSTM for time-series classification

marketvectors

Implementations for my blog post [here](https://medium.com/@TalPerry/deep-learning-the-stock-market-df853d139e02#.flflpo3xf)

maths

multivariate-time-series-forecast-using-seq2seq-in-tensorflow

poloniexr

qix

Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang

rl-stock

📈 如何用深度强化学习自动炒股

scikit-learn_bench

scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for commonly used machine learning algorithms.

seq2seq-signal-prediction

Signal prediction with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow

sru

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

stock-predict-by-rnn-lstm

Stock prediction project using Recurrent Neural Network and LSTM

storedemand