PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

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., featured with quick tracking of SOTA deep models.

Python Darts deep forecasting models

Repo containing time series forecasting solutions ranging from N-BEATS, LSTM and autoregressive models trained for predicting stock and bitcoin price.

An implementation of the N-BEATS (Neural Basis Expansion Analysis Time Series) for Interpretable trend and seasonality to forecast Bitcoin prices, demonstrating how block-based residual decomposition can capture complex cryptocurrency trends and seasonality.

Homeworks for the course Artificial Neural Networks & Deep Learning @ PoliMi.

This repository contains an introduction to the Time_series fundamentals in TensorFlow and also an end-to-end forecasting model that is going to predict the future price of Bitcoin, based on the historical price of Bitcoin. The model built in this notebook follows a supervised learning approach.

AI-powered financial forecasting and analytics system

Public copy of our engineering degree project

BitForecast is a simple project based on Time Series Data Analysis which helps to predicts/forecasts the value of bitcoin in the near future.

A comparative study of time series forecasting models, including N-BEATS Deep Learning and statistical methods (Theta, ARIMA), to predict transportation demand and vehicle trip volumes.

This repository contains the code used for my thesis on testing Network Coherency loss by Michael Lowell Hensgen on hierarchichal time series data via N-BEATS