434 Open source projects that are alternatives of or similar to cubism-es

Tidy anomaly detection

Fast & scalable MCMC for all your exoplanet needs!

Machine learning models for time series analysis

sknifedatar is a package that serves primarily as an extension to the modeltime 📦 ecosystem. In addition to some functionalities of spatial data and visualization.

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

The Open Source Time-Series Data Historian

Nonlinear Nonparametric Statistics

ZestDB

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.

A machine learning toolkit dedicated to time-series data

Visualize large time-series data in plotly

An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

Various methods for generating synthetic data for data science and ML

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

Machine Learning Projects

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

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

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

Useful tools for periodicity analysis in time series data.

LSTM Mobility Model implementation using Tensorflow

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).

CRAN R Package: Time Series Missing Value Imputation

Full Bayesian Inference for Hidden Markov Models

list of papers, code, and other resources

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

tsbox: Class-Agnostic Time Series in R

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

Dynamic Time Warping in Python / C (using ctypes)

📈 high level wrapper for parallel univariate time series forecasting 📉

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

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

playing idealized trading games with deep reinforcement learning

A framework for historical volatility estimation and analysis.

Annotation of ECG signals using deep learning, tensorflow’ Keras

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

GreyCat - Data Analytics, Temporal data, What-if, Live machine learning

R interface to Brazilian Central Bank web services

Grid Solutions Framework

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

The Most Advanced Time Series Platform

The official QuestDB website, database documentation and blog.

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.

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

Python package for automatically constructing features from multiple time series

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.

A use-case focused tutorial for time series forecasting with python

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

Scalable Time Series Data Analytics

Code for "Deep Signature Transforms" (NeurIPS 2019)

Neural network architecture for time series forecasting.

super-monorepo for machine learning and algorithmic trading

Prediction of continuous signals data and Web tracking data using dynamic Bayesian neural network. Compared with other network architectures aswell.

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

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms

Algorithms for causal inference and the detection of dynamical coupling from time series, and for approximation of the transfer operator and invariant measures.

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

Poor man's time series functionality for PostgreSQL

Creating a model to analyze and predict the trend of the prices of gold.

A Java library for Matrix Profile

Examples of Data Science projects and Artificial Intelligence use cases