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

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

Resources about time series forecasting and deep learning.

Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc.... Read more

Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone... Read more

This repository is designed to teach you, step-by-step, how to develop deep learning methods for time series forecasting with concrete and executable examples in Python.

[Advanced] Practical Statistical Inference and Machine/Deep Learning for Time Series Forecasting

An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artific... Read more

Practical Deep Learning resources for Time series analysis and forecasting

Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.