| yangwohenmai/LSTM |
1,228 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
|
Python |
| 基于LSTM的时间序列预测研究 |
| THINK989/Real-Time-Stock-Market-Prediction-using-Ensemble-DL-and-Rainbow-DQN |
125 |
|
0 |
0 |
over 2 years ago |
0 |
|
39 |
mit |
Python |
| abaranovskis-redsamurai/automation-repo |
95 |
|
0 |
0 |
about 5 years ago |
0 |
|
10 |
|
Jupyter Notebook |
| Machine learning and process automation |
| 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 |
| demmojo/lstm-electric-load-forecast |
28 |
|
0 |
0 |
over 6 years ago |
0 |
|
2 |
mit |
Python |
| Electric load forecast using Long-Short-Term-Memory (LSTM) recurrent neural network |
| bielrv/Keras-Daily-Sales-Forecast |
12 |
|
0 |
0 |
about 8 years ago |
0 |
|
1 |
|
Python |
| A Daily Sales Forecast using Keras with Tensorflow is performed. Predicted sales model take into account Day of the Week, Day of the Month, Week of the Month, Week of the Year, Year of the Month and could be easily improved using Holidays. Accuracy obtained over 92%. The current NN model has proved to improve performance over ARIMA models. |
| anandrajaram21/covidash |
6 |
|
0 |
0 |
almost 3 years ago |
0 |
|
1 |
gpl-3.0 |
Python |
| Open source, community driven, COVID-19 dashboard built with Python and Plotly Dash |
| makeyourownmaker/CambridgeTemperatureNotebooks |
5 |
|
0 |
0 |
about 2 years ago |
0 |
|
0 |
gpl-2.0 |
Jupyter Notebook |
| Cambridge UK temperature forecast python notebooks |
| tuantle/tsf |
5 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
mit |
Python |
| Neural network model creation and training for time series forecast/prediction with Keras + Tensorflow backend. |
