Reverse Dependencies of pmdarima

The following projects have a declared dependency on pmdarima:

• AI-Starter — Python library which is extensively used for all AI projects
• alpha-automl — Alpha-AutoML: NYU's AutoML System
• arbitragelab — ArbitrageLab is a collection of algorithms from the best academic journals and graduate-level textbooks, which focuses on the branch of statistical arbitrage known as pairs trading. We have extended the implementations to include the latest methods that trade a portfolio of n-assets (mean-reverting portfolios).
• auto-bots — Automated time-series forecasting
• auto-ts — Automatically Build Multiple Time Series models fast - now with Facebook Prophet!
• azureml-automl-runtime — Contains the ML and non-Azure specific common code associated with running AutoML for public use.
• azureml-training-tabular — Contains ML models, featurizers and scoring code which can either be used with AutoML or standalone.
• bigdl-chronos — Scalable time series analysis using AutoML
• bigdl-chronos-spark2 — Scalable time series analysis using AutoML
• bigdl-chronos-spark3 — Scalable time series analysis using AutoML
• bmcds — Collection of personal functions for data science
• buy-and-hold-vs-arima — buy and hold vs arima strategy
• climaticai — climaticai is a library that builds, optimizes, and evaluates machine learning pipelines
• covidify — Stay up to date with corona virus data - Download and generate reports
• darts — A python library for easy manipulation and forecasting of time series.
• diviner — Diviner: A Grouped Forecasting API
• dsna-complete — "Automate machine learning!"
• dsna-ml — "Automate machine learning"
• DXC-AI-MBN — Python library which is extensively used for all AI projects
• DXC-Industrialized-AI-Starter — Python library which is extensively used for all AI projects
• DXC-RL — Python library which is extensively used for all AI projects
• ecoform-alvin — Economic models
• econometricMethodsESAN — Economic models
• etna — ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun.
• evalml — an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions
• forecastga — A Python tool to forecast GA data using several popular timeseries models
• forecasttime — Python package to integrate the workflow of a variety of time series forecast methods
• ForeTiS — state-of-the-art and easy-to-use time series forecasting
• gdemandfcast — Generic Python Package for Time Series Forecasting.
• gdp-time-series — no summary
• grey-model — 灰色系统包，目前只有一个功能，未来会有很多！
• habitat-fydp-package — Democratize access to HAB related data in Lake Erie to be used for scientific research
• hts-forecast — AUTO HIERARCHIAL TIME SERIES FORECASTING
• kf-d3m-primitives — All Kung Fu D3M primitives as a single library
• lazyforecast — LazyForecast is a Python library for performing univariate time series analysis using a lazy forecasting approach. This approach is designed to provide quick and simple forecasting models without requiring extensive configuration or parameter tuning.
• lottokit — Lotto Kit Package
• lyzr — no summary
• mlflavors — MLflavors: A collection of custom MLflow flavors.
• newstrends — Tools for modeling news
• ostatslib — Open Statistical Analysis Agent Library
• proloaf — A Probabilistic Load Forecasting Project.
• pyanomaly — Time series anomaly detection in Python
• pycaret — PyCaret - An open source, low-code machine learning library in Python.
• pycaret-ts-alpha — PyCaret - An open source, low-code machine learning library in Python.
• pyhydroqc — A package containing functions for anomaly detection and correction of aquatic sensor data.
• pystocktopus — help you maintain your stock dashboard also predict future for a stock based upon past data and also use the news sentiments of stocks volatality
• PyThief — Python verison of Thief forecasting.
• scikit-hts — Hierarchical Time Series forecasting
• sforecast — A framework for running forecasting models within a sliding/expanding window out-of-sample forecast fit (train/test) and prediction (forecasts). The package includes support of classical forecasting models, SK Learn supervised learning ML models, and TensorFlow deep learning models.
• skforecast — Forecasting time series with scikit-learn regressors. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM, XGBoost, Ranger...).
• sktime — A unified Python toolbox for machine learning with time series
• sphynxml — no summary
• statsforecast — Time series forecasting suite using statistical models
• tbats — BATS and TBATS for time series forecasting
• ThymeBoost — Gradient boosted time series decomposition for forecasting.
• timemachines — Evaluation and standardization of autonomous time series prediction
• timeseria — An object-oriented time series processing library
• timexseries — TIMEX is a framework for time-series-forecasting-as-a-service.
• timexseries-clustering — TIMEX-CLUSTERING is a framework for time-series-clustering-as-a-service
• TrilabytePyML — Trilabyte Python Machine Learning
• tsf — A library to forecast timeseires data
• tsforecasting — TSForecasting is an Automated Time Series Forecasting Framework
• u8darts — A python library for easy manipulation and forecasting of time series.
• u8timeseries — A collection of easy-to-use timeseries forecasting models
• vital-sqi — Signal quality control pipeline for electrocardiogram and photoplethysmogram
• vo-wot — Virtual Object python implementation using a W3C WoT Runtime and the WoT Scripting API
• witcher — Automated AI tool including: recommender system, deep Learnings ...