Popular GitHub Repositories for Sarimax

In this notebook, we will create an AI and time serie driven forecasting engine based on a set of 5 AI models and 5 time series models and employ several algorithms to perform feature engineering and selection on a multivariate time series dataset.

S&P500 Stock Index Movement Forecastor with various Statistical and Machine Learning Models

Forecasting future sales of a product offers many advantages. Predicting future sales of a product helps a company manage the cost of manufacturing and marketing the product. In this notebook, I will try to you through the task of future sales prediction with machine learning using Python.

Forecasting building energy demand through time series analysis and machine learning.

This project aims to investigate temperature changes over time and predict future temperature patterns on a regional and global scale. We employ time series forecasting methods, including neural networks, ARIMA, and SARIMAX, using the GISTEMP v4 dataset from NA

This is the public repository for some tasks that I performed as an Intern (PAT) at Cognizant Technology Solutions. All these projects and tasks are based on AI ML, and involve topics ranging from NLP to time-series analysis, beginner to advanced topics in the field of AI ML.

???? Welcome to ForecastAIHub! Our repository is dedicated to financial market prediction and flight passenger forecasting. By harnessing powerful AI algorithms, we provide accurate forecasts for market trends and flight demand. ???? Our mission is to empower data-driven decision-making in the realms of finance and aviation.

Predict the future of your network using the best time series ML model that fit with your traffic.

Leveraged Machine Learning to perform Time Series Analysis and forecast housing prices in Miami-Dade County. The end goal was to identify and recommend the top 5 zip codes that are predicted to see the highest growth in average home value.

This advanced forecasting tool leverages Prophet, ARIMA, SARIMA, and LSTM models to predict daily sales for 32 pizzas and 64 ingredients. With Prophet achieving the lowest MAPE, it ensures accurate demand forecasts, optimized inventory, and efficient purchase planning, reducing waste, preventing stockouts, and enhancing supply chain efficiency.

This Project analyses the carbon footprint of the U.S. commercial sector using three machine learning models. A combination of energy consumption data and carbon dioxide emission data was used to achieve the carbon footprint variable.

Sales Forecasting with Time Series Analysis by using ARIMA and SARIMAX.

Machine Learning / Deep learning : Forecasting customer transactions for future timesteps

A repository with notebooks to help understand time series forecasting, with projects to practise.

A comparative breakdown of traditional econometric timeseries models vs. more modern ML methods for predicting a retail firm's sales over a short to medium horizon