| LongxingTan/Time-series-prediction |
762 |
|
0 |
0 |
over 2 years ago |
11 |
October 16, 2023 |
11 |
mit |
Python |
| tfts: Time series deep learning models in TensorFlow |
| philipperemy/n-beats |
686 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
Python |
| Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. |
| JEddy92/TimeSeries_Seq2Seq |
362 |
|
0 |
0 |
almost 7 years ago |
0 |
|
9 |
|
Jupyter Notebook |
| This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow. |
| mikekeith52/scalecast |
292 |
|
0 |
0 |
about 2 years ago |
186 |
December 04, 2023 |
39 |
mit |
Python |
| The practitioner's forecasting library |
| kristpapadopoulos/seriesnet |
202 |
|
0 |
0 |
almost 4 years ago |
0 |
|
0 |
mit |
Python |
| Time series prediction using dilated causal convolutional neural nets (temporal CNN) |
| curiousily/Deep-Learning-For-Hackers |
196 |
|
0 |
0 |
almost 6 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT) |
| albertogaspar/dts |
157 |
|
0 |
0 |
almost 3 years ago |
0 |
|
5 |
mit |
Python |
| A Keras library for multi-step time-series forecasting. |
| LenzDu/Kaggle-Competition-Favorita |
138 |
|
0 |
0 |
about 8 years ago |
0 |
|
5 |
mit |
Python |
| 5th place solution for Kaggle competition Favorita Grocery Sales Forecasting |
| nabeel-oz/qlik-py-tools |
132 |
|
0 |
0 |
about 5 years ago |
0 |
|
17 |
mit |
Python |
| Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE). |
| MarlonCajamarca/Keras-LSTM-Trajectory-Prediction |
81 |
|
0 |
0 |
over 3 years ago |
0 |
|
1 |
|
Python |
| A Keras multi-input multi-output LSTM-based RNN for object trajectory forecasting |
