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time-series-forecasting

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gluon-ts

awslabs / gluon-ts

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Alro10 / deep-learning-time-series

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 Nov 11, 2021
  • Jupyter Notebook

curiousily / Getting-Things-Done-with-Pytorch

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Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

nlp machine-learning tutorial computer-vision deep-learning time-series sentiment-analysis pytorch transformer lstm yolo face-recognition face-detection object-detection transfer-learning bert anomaly-detection time-series-forecasting coronavirus time-series-anomaly-detection
  • Updated Jun 14, 2021
  • Jupyter Notebook
flow-forecast

AIStream-Peelout / flow-forecast

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curiousily / Deep-Learning-For-Hackers

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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)

python machine-learning deep-learning sentiment-analysis tensorflow keras artificial-intelligence neural-networks object-detection jupyter-notebooks autoencoders tensorflow-tutorial bert image-augmentation anomaly-detection time-series-classification time-series-forecasting lstms intent-recognition
  • Updated Apr 23, 2020
  • Jupyter Notebook
eland

elastic / eland

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