| jaungiers/LSTM-Neural-Network-for-Time-Series-Prediction |
4,220 |
|
0 |
0 |
about 3 years ago |
0 |
|
47 |
agpl-3.0 |
Python |
| LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data |
| ScottfreeLLC/AlphaPy |
1,003 |
|
0 |
0 |
over 2 years ago |
25 |
August 29, 2020 |
13 |
apache-2.0 |
Python |
| Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost |
| kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis |
460 |
|
0 |
0 |
about 2 years ago |
0 |
|
21 |
mit |
Python |
| Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall |
| AlgoTraders/stock-analysis-engine |
414 |
|
0 |
0 |
over 5 years ago |
167 |
September 05, 2020 |
6 |
|
Jupyter Notebook |
| Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/ |
| hichenway/stock_predict_with_LSTM |
286 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| Predict stock with LSTM supporting pytorch, keras and tensorflow |
| THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN |
125 |
|
0 |
0 |
over 2 years ago |
0 |
|
39 |
mit |
Python |
| liyinwei/copper_price_forecast |
73 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
gpl-3.0 |
Python |
| copper price(time series) prediction using bpnn and lstm |
| philipperemy/stock-volatility-google-trends |
70 |
|
0 |
0 |
about 4 years ago |
0 |
|
1 |
|
Python |
| Deep Learning Stock Volatility with Google Domestic Trends: https://arxiv.org/pdf/1512.04916.pdf |
| z331565360/State-Frequency-Memory-stock-prediction |
69 |
|
0 |
0 |
about 7 years ago |
0 |
|
11 |
|
Python |
| Originate/dbg-pds-tensorflow-demo |
65 |
|
0 |
0 |
about 6 years ago |
0 |
|
3 |
mit |
Jupyter Notebook |
| Making predictions on prices in the Deutsche Börse Public Dataset using neural networks |
