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time-series-prediction

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gluon-ts

awslabs / gluon-ts

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Alro10 / deep-learning-time-series

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List of papers, code and experiments using deep learning for time series forecasting

deep-neural-networks deep-learning time-series tensorflow prediction python3 pytorch recurrent-neural-networks lstm series-analysis forecasting-models lstm-neural-networks demand-forecasting series-forecasting sales-forecasting time-series-classification time-series-prediction time-series-forecasting series-classification forecasting-competitions
  • Updated Sep 13, 2020
  • Jupyter Notebook

regel / loudml

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K-Fold cross-validation

regel
regel commented Feb 25, 2019

Cross validation is a technique for assessing how the statistical analysis generalises to an independent data set.It is a technique for evaluating machine learning models by training several models on subsets of the available input data and evaluating them on the complementary subset of the data. Using cross-validation, there are high chances that we can detect over-fitting with ease.

The f

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good first issue help wanted

kennedyCzar / FORECASTING-1.0

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Predictive algorithm for forecasting the mexican stock exchange. Machine Learning approach to forecast price and Indicator behaviours of MACD, Bollinger and SuperTrend strategy

neural-networks forecasting rnn lightgbm adaboost fibonacci-series prophet forecasting-models ema rsi time-series-analysis facebook-prophet-forecasting time-series-prediction macd relative-strength-index time-series-forecasting facebook-prophet signal-generator supertrend pivot-point
  • Updated Mar 28, 2020
  • Python

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