A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

If you can measure it, consider it predicted

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Time series forecasting models for web traffic forecasting

Real time streaming of a time series with corresponding forecasts.

SARIMAX model for forecast traffic volume

A complete end-to-end time series forecasting project analyzing Global Superstore sales data with EDA, statistical diagnostics, SARIMA modeling, and actionable business insights.

An ML-powered web app to predict cloud data consumption of a SaaS system user using Time Series Forecasting (TSF)

Time Series Analysis and Visualization of Earth Surface Temperature using Berkeley Earth Data by building a Machine Learning Model in Python

Complete data-ML pipeline for forecast model of electricity consumption in Victoria

Time Series Analysis and Forecasting: Use SARIMAX to Predict Customer Complaints

Base Docker images used with the pmdarima repo

SARIMAX forecast tool: Python demo web app with Streamlit

Time series data analysis, decomposition, and forecasting using Python libraries to forecast future values of poverty rates across various countries.

Predicting Walmart Sales and Performing Exploratory Data Analysis

Time series analysis and forecasting (ARIMA, ETS, LSTM, Prophet) of stock prices.

Time series forecasting of telecom revenue using Auto-ARIMA and walk-forward validation.

Tool for benchmarking automated time series forecasting algorithms

Análisis y pronóstico de series temporales de NO₂ y CO en Madrid (2001-2018). Aplicación de ARIMA y métodos de suavizado exponencial (SES, Holt, Holt-Winters) con evaluación mediante métricas de error.

Predictive modeling of Tesla stock prices using AR, MA, ARIMA, and LSTM models. This project leverages Python for time series analysis, statistical forecasting, and deep learning techniques.