1089 Open source projects that are alternatives of or similar to time-series-classification

Timeseries database

R library for data.world

Python package for automatically constructing features from multiple time series

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global…

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

Renewcast: Forecasting Renewable Electricity Generation in EU Countries.

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Case studies, examples, and exercises for learning to deploy ML models using AWS SageMaker.

A python library for easy manipulation and forecasting of time series.

ES6 module of cubism.js, based on d3v5.

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.

list of papers, code, and other resources

RNN based Time-series Anomaly detector model implemented in Pytorch.

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.

RRDtool 1.x - Round Robin Database

playing idealized trading games with deep reinforcement learning

Examples for usage of Mindsdb https://www.mindsdb.com/

tsbox: Class-Agnostic Time Series in R

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

The Most Advanced Time Series Platform

Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow

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.

A Python toolkit for rule-based/unsupervised anomaly detection in time series

Python package for data.world

GANs for time series generation in pytorch

A highly scalable real-time graphing system

An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

Machine Learning on Sequential Data Using a Recurrent Weighted Average

High-performance time-series aggregation for PostgreSQL

Quantitative Financial Modelling Framework

sknifedatar is a package that serves primarily as an extension to the modeltime 📦 ecosystem. In addition to some functionalities of spatial data and visualization.

Time Series Benchmark Suite, a tool for comparing and evaluating databases for time series data

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

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

Time Series in Go and PostgreSQL

A python library for time-series smoothing and outlier detection in a vectorized way.

Fully Convlutional Neural Networks for state-of-the-art time series classification

LSTM Mobility Model implementation using Tensorflow

SiriDB is a highly-scalable, robust and super fast time series database. Build from the ground up SiriDB uses a unique mechanism to operate without a global index and allows server resources to be added on the fly. SiriDB's unique query language includes dynamic grouping of time series for easy analysis over large amounts of time series.

Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

SpectroChemPy is a framework for processing, analyzing and modeling spectroscopic data for chemistry with Python

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

Miami InSAR time-series software in Python

Poor man's time series functionality for PostgreSQL

A duplicate-free variant of the CIFAR test set.

several utilities to help wrangle COVID-19 data into a time-series format

A Python tool for estimating velocity and time-series from Interferometric Synthetic Aperture Radar (InSAR) data.

Information of public available data sets for biomechanics.

A unified framework for machine learning with time series

Extensible time series class that provides uniform handling of many R time series classes by extending zoo.

sktime companion package for deep learning based on TensorFlow

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

Annotation of ECG signals using deep learning, tensorflow’ Keras

🚓 Crime dataset for the City of Buenos Aires, Argentina

The Prometheus monitoring system and time series database.

Grid Solutions Framework

Forecast time series and stock prices with SCINet

Clothing detection dataset