If you can measure it, consider it predicted

Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|

Lstm Neural Network For Time Series Prediction | 4,220 | a year ago | 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 | ||||||||||

Dl Workshop Series | 935 | 7 months ago | 1 | apache-2.0 | Jupyter Notebook | |||||

Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT) | ||||||||||

Time Series Prediction | 762 | 6 months ago | 11 | October 16, 2023 | 11 | mit | Python | |||

tfts: Time series deep learning models in TensorFlow | ||||||||||

N Beats | 686 | a year ago | mit | Python | ||||||

Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. | ||||||||||

Audio Classification | 398 | 2 years ago | 16 | mit | Jupyter Notebook | |||||

Code for YouTube series: Deep Learning for Audio Classification | ||||||||||

Lstm Fcn | 388 | 5 years ago | 7 | Python | ||||||

Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification | ||||||||||

Microprediction | 312 | 9 | 6 months ago | 205 | January 26, 2023 | 22 | Jupyter Notebook | |||

If you can measure it, consider it predicted | ||||||||||

Lotteryprediction | 261 | 6 months ago | other | Jupyter Notebook | ||||||

:full_moon_with_face: Lottery prediction besides of following "law of proability","Probability: Independent Events", there are still "Saying "a Tail is due", or "just one more go, my luck is due to change" is called The Gambler's Fallacy" existed. | ||||||||||

Mlstm Fcn | 241 | 4 years ago | 5 | Python | ||||||

Multivariate LSTM Fully Convolutional Networks for Time Series Classification | ||||||||||

Seriesnet | 202 | 2 years ago | mit | Python | ||||||

Time series prediction using dilated causal convolutional neural nets (temporal CNN) |

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