A unified framework for machine learning with time series

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

A toolkit for time series machine learning and deep learning

DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow

PyTorch code for Learning Deep Time-index Models for Time Series Forecasting (ICML 2023)

A fast canonical-correlation-based search algorithm for feature selection, system identification, data pruning, etc.

Predict the trajectory of the vehicles in HCM city streets with YOLOv7 + DeepSORT + CNN-LSTM/CNN-GRU.

Time series analysis with LLM-ABBA: A symbolic approach

Deep Learning for Skeleton Based Human Motion Rehabilitation Assessment: A Benchmark

A toolkit for time series machine learning algorithms that don't fit in aeon. Use aeon instead if you can!

Collection of my Time series Analysis Projects

NARX Pytorch implementation

This repository contains files and scripts to build a sales forecasting Telegram Bot for a pharmacy chain. The purpose of this project is to quickly and easily provide a revenue estimate in order to assist the CEO in decision making. (Project Data Science in Production / DS Community)

MarketSent is an AI-driven platform that analyzes financial sentiment from news headlines, social media posts, and market data. It uses Natural Language Processing (NLP) and machine learning to detect investor mood, predict market volatility, and visualize sentiment over time.

Time Series Regression Models

This project analyses the effect of one-year momentum factor on stock returns by computing CAPM, the Fama-French 3-factor model, and a 4-factor model accounting for momentum. The persistence of the momentum effect through the cross-sectional Fama/MacBeth regression is tested to assess whether this factor can explain test asset returns.

Generalization of the Prais Winsten estimator for AR time series of arbitrary order

The experiment scripts of the TARNet model for classification of time series with missing balues

Predictive modeling system for seasonal bulb removal timing using Growing Degree Days (GDD) and Easter date regression.