638 Open source projects that are alternatives of or similar to Deepadots

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.

Extending broom for time series forecasting

Durable time-series database that's API-compatible with Prometheus.

Anomaly detection

📈 A small, fast chart for time series, lines, areas, ohlc & bars

NeuralProphet - A simple forecasting model based on Neural Networks in PyTorch

Stock Analysis Tutorial in Python

Financial market technical analysis & indicators in Julia

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.

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

If you can measure it, consider it predicted

Hastic data management server for analyzing patterns and anomalies from Grafana

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

Merlion: A Machine Learning Framework for Time Series Intelligence

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.

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

A machine learning toolkit dedicated to time-series data

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

Library which contains several time-dependent data and index structures (e.g., IntervalTree, BucketTimeSeries), as well as algorithms.

Time-aware tibbles

Anomaly detection for temporal data using LSTMs

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

A friendly package for Kepler & TESS time series analysis in Python.

Resources for working with time series and sequence data

fast implementation of singular spectrum transformation (change point detection algorithm)

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Bringing financial analysis to the tidyverse

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

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Calculates the Hurst exponent of a time series based on Rescaled range (R/S) analysis.

Solution to Kaggle - Web Traffic Time Series Forecasting

Timeseries database

Java implementation of Seasonal-Trend-Loess time-series decomposition algorithm.

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.

GridDB is a next-generation open source database that makes time series IoT and big data fast,and easy.

[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

1st place solution

Anything can happen in the next half hour (including spectral timing made easy)!

An End-to-end Outlier Detection System

List of tools & datasets for anomaly detection on time-series data.

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

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

A Multipurpose Library for Synthetic Time Series Generation in Python

An open-source library of algorithms to analyse time series in GPU and CPU.

Downsample plugin for Flot charts.

Time series analysis in Java

High-performance time series algorithms for Ruby

Predict time-series with one line of code.

Sherlock is an anomaly detection service built on top of Druid

Anomaly detection for streaming time series, featuring automated model selection.

An Open Source Distributed Time Series Database with high performance, high compression ratio and high usability.

Collection of several downsampling methods for time series visualisation purposes.

An open-source, low-code machine learning library in Python

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

A toolkit for working with time series in R

A python library for Bayesian time series modeling

Implementation of time series compression method from the Facebook's Gorilla paper

Time Series Ensemble Forecasting

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

Tidy anomaly detection