545 Open source projects that are alternatives of or similar to tsfuse

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

Time Series Forecasting Best Practices & Examples

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Merlion: A Machine Learning Framework for Time Series Intelligence

The AI Application Platform We All Need. Human AND Machine Intelligence. Based on experience building AI solutions at Panasonic: robotics predictive maintenance, cold-chain energy optimization, Gigafactory battery mfg, avionics, automotive cybersecurity, and more.

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.

A simplified version of featuretools for Spark

Python package for early warning signals (EWS) of bifurcations in time series data.

An open source python library for automated feature engineering based on Genetic Programming

PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA

Dynamic Time Warping in Python / C (using ctypes)

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LSTM Mobility Model implementation using Tensorflow

Statistical inference on machine learning or general non-parametric models

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Official code for UnICORNN (ICML 2021)

Example of order book modeling.

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Predict time-series with one line of code.

Black-box optimization library

An up-to-date & curated list of Awesome IMU-based Human Activity Recognition(Ubiquitous Computing) papers, methods & resources. Please note that most of the collections of researches are mainly based on IMU data.

An integrated framework in R for textual sentiment time series aggregation and prediction

Time Series Ensemble Forecasting

Renewcast: Forecasting Renewable Electricity Generation in EU Countries.

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An OpenTSDB-like time series database, with much better performance.

Bayesian Generalized Linear Models with Time-Varying Coefficients

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Using LSTM network for time series forecasting

GreyCat - Data Analytics, Temporal data, What-if, Live machine learning

Historical NAV/price/time-series data of mutual funds and popular benchmark indices in India

Prediction of continuous signals data and Web tracking data using dynamic Bayesian neural network. Compared with other network architectures aswell.

An overview of univariate time series forecasting models with sample code.

PyTorch implementations of neural networks for timeseries classification

Forecast time series and stock prices with SCINet

COVID-19 spread shiny dashboard with a forecasting model, countries' trajectories graphs, and cluster analysis tools

Scalable machine 🤖 learning for time series forecasting.

Time series market data

PlotTwist - a web app for plotting and annotating time-series data

An automatic machine learning system

This repo is about NAS

Wavefront Proxy Project

A Java library for Matrix Profile

Sberbank Data Science Jorney Auto-ML competition

Reusable CNN and RNN model doing time series binary classification

Probably the best curated list of data science books in Python

Code examples for pyFTS

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Creating a model to analyze and predict the trend of the prices of gold.

💹 SIMON is powerful, flexible, open-source and easy to use machine learning knowledge discovery platform 💻

Data visualization tool for wikis evolution

MTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)

If you can measure it, consider it predicted

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

Time series implementation in Go

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Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.