This is a price uni and multivariate forecasting of collectible assets indices using ARIMA models

Implementation and comparison of ARIMA models to forecast Olist revenue for the next 14 days.

In this project I present the US weekly retail sales forecast from the USDA's Economic Research Service (ERS) report.

Julia Package with SARIMA model implementation using JuMP.

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

In this project, I thoroughly clean bike-share data from 2014-2015 and build a simplistic ARIMA model to forecast daily revenue per bike station in 2016. (Repo in progress)

Time series forecasting using 8 different models

*Finished* Time Series Analysis & Forecasting for a variety of datasets

This project aims to analyze and forecast daily revenue and the daily number of receipts across six distinct restaurants, by employing a statistical approach and utilizing predictive models, particularly the SARIMA and TBATS models.

A Time series Data modelling to forecast Gambling Addiction Signs in Players using K-Means Clustering, ARIMA/SARIMA and LSTM to forecast wagering patterns

Data Science: Machine Learning analysis of B2B website Visits and Purchase Patterns

Auto-Forecasting is a web application that takes in an excel file with univariate time series data and provides forecasts. Auto-Forecasting works on SARIMA modeling.

Time series modelling with extended regression SARIMA models

Pharmalytics is a sales prediction application for Firstmed Pharmacy using the SARIMA model and Streamlit.

Este repositorio contiene un análisis exhaustivo de las sobredosis de opioides en Estados Unidos, un problema de salud pública que ha alcanzado proporciones alarmantes en las últimas décadas. A través de una combinación de datos estadísticos, visualizaciones informativas y análisis en profundidad. 💉🩺

Recently inflation is a popular topic in Poland and is highest since 2001. Experts presume inflation in Poland should continue to rise, and by the end of 2021 it will be close to 8%. This notebook aims to develop a forecasting model for time series using Python.

Arima, Sarima, LSTM, Prophet, DeepAR, Kats, Granger-causality, Autots

Here is a time series analysis using R and Arima models to predict air traffic for Hong Kong Airport.

This project focuses on Time Series Analysis techniques, uncovering patterns and leveraging forecasting models to predict future sales trends.

Timeseries analysis of Wikipedia traffic prediction using ARIMA, SARIMA and Prophet models.