This is a neural network that I wrote for the Mathworks Math Modeling Challenge in 2023. The purpose of this code is to take in statistics about ebike sales and other factors that could change it. The point of the neural network is to find the weights for each factor, and thus find how much each factor impacts the ebike sales

Data Science project for forecasting steel and crude oil prices

Unravelling Crime Trends with ARIMA & SARIMA Analysis in a Crime Series

A TimeSeries Prediction App which predicts the future web traffic of the lacity web app

Time Series With Python

Regression and Time Series course at IIT KGP

COVID-19 is one of the most pandemic problems today, many countries suffer tohandle COVID-19 problems. Data mining techniques provide a good quality tool for improving manual analysis identification COVID19 cases per day, deaths per day and number of patients cured per day.

Time-series stock market prediction model using updated ARIMA algorithms

Penr-oz Covid-19 Forecaster

Forecast future electricity by ARIMA moedel

[ONGOING] Final year Major Project

SmoothTrend is a comprehensive time series analysis tool that utilizes Holt-Winters, Holt, and Simple Exponential Smoothing methods, as well as ARIMA modeling, to perform advanced trend analysis, stationarity testing, residual analysis, and forecasting.

Analysis of Emergency Deparment Visits and Admissions for Influenza-like Illness and/or Pneumonia in New York City

How to make forecast with python ? I develop a software that allows to : - Make commercial forecasts from a history - Compare several forecasting methods - Display the results (forecasts and comparison)

Demonstration of time series analysis using various concepts and models.

Building a projection of the business potential for each of the 4000 regions for the next 15 months using time series forecasting techniques.

Techniques for forecasting multiple time series: an application of computer intelligence techniques for school enrollment projections.

Predicting JOLTS data with Real GDP as input variable using ARIMA Model

AutoARIMA for appreciating time series analysis of several stocks in the cryptomarket.