420 Open source projects that are alternatives of or similar to ahead

Imhotep is a large-scale analytics platform built by Indeed.

Scientific time series and deep learning state of the art

Renewcast: Forecasting Renewable Electricity Generation in EU Countries.

Tidy anomaly detection

1st place solution

Machine learning models for time series analysis

Time series annotation library.

Deep Learning API and Server in C++14 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

Fast & scalable MCMC for all your exoplanet needs!

Nonlinear Nonparametric Statistics

ES6 module of cubism.js, based on d3v5.

Process live and historical data from luftdaten.info, IRCELINE and OpenAQ. Filter by station-id, sensor-id and sensor-type, apply reverse geocoding, store into timeseries and RDBMS databases, publish to MQTT, output as JSON or visualize in Grafana.

The Open Source Time-Series Data Historian

Visualize large time-series data in plotly

ZestDB

Various methods for generating synthetic data for data science and ML

A machine learning toolkit dedicated to time-series data

Machine Learning Projects

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

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

Useful tools for periodicity analysis in time series data.

Statistical Models with Regularization in Pure Julia

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).

StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.

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.

Using LSTM network for time series forecasting

Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs

CRAN R Package: Time Series Missing Value Imputation

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

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

📈 high level wrapper for parallel univariate time series forecasting 📉

tsbox: Class-Agnostic Time Series in R

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

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

A framework for historical volatility estimation and analysis.

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

A flexible data historian based on InfluxDB, Grafana, MQTT and more. Free, open, simple.

list of papers, code, and other resources

R interface to Brazilian Central Bank web services

Annotation of ECG signals using deep learning, tensorflow’ Keras

[Implementation example] Attend and Diagnose: Clinical Time Series Analysis Using Attention Models

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

The official QuestDB website, database documentation and blog.

Grid Solutions Framework

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

playing idealized trading games with deep reinforcement learning

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.

Carbon is one of the components of Graphite, and is responsible for receiving metrics over the network and writing them down to disk using a storage backend.

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

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 use-case focused tutorial for time series forecasting with python

Python implementation of AutoPlait (SIGMOD'14) without smoothing algorithm. NOTE: This repository is for my personal use.

Classifying time series using feature extraction

midasml package is dedicated to run predictive high-dimensional mixed data sampling models

Synthetic Data Generation for mixed-type, multivariate time series.

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

Automated Time Series Forecasting

Open source time series library for Python

Bringing financial analysis to the tidyverse