The Prometheus monitoring system and time series database.

LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.

High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios

A time-series database for high-performance real-time analytics packaged as a Postgres extension

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

QuestDB is a high performance, open-source, time-series database

VictoriaMetrics: fast, cost-effective monitoring solution and time series database

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

A Library for Advanced Deep Time Series Models for General Time Series Analysis.

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

A unified framework for machine learning with time series

A python library for user-friendly forecasting and anomaly detection on time series.

Automatic extraction of relevant features from time series:

Pretty time-series line graphs

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

The Time Series Visualization Tool that you deserve.

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

Probabilistic time series modeling in Python

Chronos: Pretrained Models for Time Series Forecasting

A scalable, distributed Time Series Database.

Cubism.js: A JavaScript library for time series visualization.

Time series forecasting with PyTorch

Merlion: A Machine Learning Framework for Time Series Intelligence

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

Cube: A system for time series visualization.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

In-memory dimensional time series database.

Time Series Alerting Framework