timeseries

Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

tfts: Time Series Deep Learning Models in TensorFlow

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 InfluxDB Client for Node.js and Browsers

Golang implementation of Graphite/Carbon server with classic architecture: Agent -> Cache -> Persister

Chart.js module for charting financial securities

InfluxDB 2.0 python client

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

High-quality pro audio resampler / sample rate conversion header-only C++ library. Very fast, for both audio resampling and time-series interpolation.

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

Intuitive Data Workflows

A simple and flexible code for Reservoir Computing architectures like Echo State Networks

Time series analysis in the `tidyverse`

Fast data store for Pandas time-series data

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

Real-time anomaly detection for time series metrics. 11 years of production anomaly detection evolution. Multi-algorithm ensembles. Pattern recognition using semi-supervised and unsupervised learning. Correlation analysis. Learns and gets better over time. No GPU required, can run on a VPS.

Modeltime unlocks time series forecast models and machine learning in one framework

Plot in the terminal using braille dots.

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

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.