569 Open source projects that are alternatives of or similar to khiva-ruby

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

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

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

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

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.

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

STUMPY is a powerful and scalable Python library for modern time series analysis

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

Resources for working with time series and sequence data

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.

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

A Java library for Matrix Profile

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

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

Tidy anomaly detection

An End-to-end Outlier Detection System

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.

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

Merlion: A Machine Learning Framework for Time Series Intelligence

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

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

R Functions implementing UCR Matrix Profile 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).

A data preprocessing package for time series data. Design for machine learning and deep learning.

THIS REPO HAS MOVED TO https://github.com/apache/incubator-iotdb. TsFile is a columnar file format designed for time-series data, which supports efficient compression and query. It is easy to integrate TsFile with your IOT big data processing frameworks.

Code used in the paper "Time Series Clustering via Community Detection in Networks"

The official QuestDB website, database documentation and blog.

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

OpenSnitch is a GNU/Linux application firewall

This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

A Keras library for multi-step time-series forecasting.

ADRepository: Real-world anomaly detection datasets

Generalized Method of Wavelet Moments (GMWM) is an estimation technique for the parameters of time series models. It uses the wavelet variance in a moment matching approach that makes it particularly suitable for the estimation of certain state-space models.

Exponential Smoothing & Moving Average Models in Java

Full Bayesian Inference for Hidden Markov Models

📈 high level wrapper for parallel univariate time series forecasting 📉

GPU-Accelerated Deep Learning for Time Series using Modeltime GluonTS (Learning Lab 53). Event sponsors: Saturn Cloud, NVIDIA, & Business Science.

An R package for space-time anomaly detection using scan statistics.

MODIS Assimilation and Processing Engine

CentOS based Docker container for Time Series Analysis and Modeling.

Code for "Deep Signature Transforms" (NeurIPS 2019)

Official codes for CVPR2021 paper "MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection"

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

A fast, scalable and light-weight C++ Fréchet distance library, exposed to python and focused on (k,l)-clustering of polygonal curves.

super-monorepo for machine learning and algorithmic trading

📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈

Deploying a Batch Scoring Pipeline for Python Models

Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

A Julia implementation of basic tools for time series analysis compatible with incomplete data.

Useful tools for periodicity analysis in time series data.

Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural Network

Benchmark for DeepLearning anomaly detection

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

A framework for historical volatility estimation and analysis.

Time series competition data

Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"

Analyzes chronological patterns present in time-series data and provides human-readable descriptions

benfordslaw is about the frequency distribution of leading digits.