wyjend's starred repositories
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
lihang-code
《统计学习方法》的代码实现
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
awesome-quant
**的Quant相关资源索引
adversarial
Code and hyperparameters for the paper "Generative Adversarial Networks"
tuning_playbook_zh_cn
一本系统地教你将深度学习模型的性能最大化的战术手册。
improved_wgan_training
Code for reproducing experiments in "Improved Training of Wasserstein GANs"
ai_quant_trade
股票AI操盘手：从学习、模拟到实盘，一站式平台。包含股票知识、策略实例、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易
Stock-price-prediction-using-GAN
In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.
neural-cryptography-tensorflow
Neural Networks that invent their own encryption :key:
tensorflow-infogan
:dolls: InfoGAN: Interpretable Representation Learning
DeepMIMO-matlab
DeepMIMO dataset and codes for mmWave and massive MIMO applications
Channel_Estimation_cGAN
Channel Estimation for One-Bit Multiuser Massive MIMO Using Conditional GAN
A-Stock-Prediction-System-with-Deep-Learning
Try to predict stock price with LSTM、GAN and DRL, exploring the features of news and technical indicators，which help improving perfomance of predictions.
stock_market_GAN
Reproduction of code described in the paper "Stock Market Prediction Based on Generative Adversarial Network" by Kang Zhang et al.
MHGAN-Tensorflow
Metropolis-Hastings GAN in Tensorflow for enhanced generator sampling
Pix2Pix-eager
Tensorflow eager implementation of Pix2Pix (Image-to-image translation with conditional adversarial networks)