longfly04

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.

Awesome-Papers-and-Codes

Some flash thoughts that smell good in Deep learning，Graph network， Mento Carlo Searching and so on .

lab1-deploy-tidb-cluster-on-aws-eks

lab2-cloud-service-availability

obsidian-pic-Picgo

python-1

Show Me the Code Python version.

Quantitative-trading-system-of-stock-market-based-on-deep-learning

Quantitative analysis with deep learning prediction and reinforcement learning transactions.

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.

tenderingscrapy

Scrapy tendering and bidding goods data in government procurement of QingDao.

Traffic-flow-forecast

Using GAT with temporal attention to forecast urban traffic flow.

longfly04/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.

longfly04/Quantitative-trading-system-of-stock-market-based-on-deep-learning

Quantitative analysis with deep learning prediction and reinforcement learning transactions.

longfly04/Traffic-flow-forecast

Using GAT with temporal attention to forecast urban traffic flow.

longfly04/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.

longfly04/tenderingscrapy

Scrapy tendering and bidding goods data in government procurement of QingDao.

longfly04/Awesome-Papers-and-Codes

Some flash thoughts that smell good in Deep learning，Graph network， Mento Carlo Searching and so on .

longfly04/lab1-deploy-tidb-cluster-on-aws-eks

longfly04/lab2-cloud-service-availability

longfly04/obsidian-pic-Picgo

longfly04/python-1

Show Me the Code Python version.

longfly04/vue_elementUI_Rating