MLOPS folder for SNAPE deployment

Data analysis project on an Udemy wikipedia visits database using Python

Monelytics is a web-based platform utilizing Python for stock prediction purposes. It compares approximately nine machine learning and deep learning models and can predict the closing prices of the big four Indonesian banks

This project utilizes Prophet, a powerful forecasting tool developed by Facebook, to predict seasonal sales patterns. Leveraging time series analysis techniques, the project aims to forecast the seasons of the year with the highest sales.

Amazon SageMaker Local Mode Examples

Predicting glucose levels of diabetes patients using the Neural Prophet model alongside with the Dexcom Clarity Overview reports in order for users to have an idea of their future glucose levels.

A repository for developing winter predictions and forecasts

Code by @drasbaek and @MinaAlmasi for the exam in "Data Science, Prediction, and Forecasting" (F2024) at the Cognitive Science MSc.

Capstone Project 4th year - Computing and IT - Welcome to the Crime Rate Forecasting in Ireland repository! This project focuses on predicting crime rates in specific areas across Ireland using time series forecasting models.

Time Series Analysis of Covid-19 Dataset

A forecasting system for multiple sectors that uses ARIMA, ETS, SVR, and other models displayed on a user friendly interface with different viewing options.

Sales prediction models for Electronic Vehicles in USA

An end-to-end application for crime rate detection and crime type classification

Code Repository

Time Series Analysis model application

The "Cincinnati Traffic Crashes - Time Series Analysis" is a comprehensive study that employs statistical techniques to examine patterns and trends in traffic accidents over time within the Cincinnati area. This analysis aims to forecast future incidents, and assist in developing strategies to enhance road safety.

This project is based on supply chain analytics along with demand forecasting and inventory management of the top selling product. Demand forecasting is done by using the prophet time series model. Also, the dashboard consists of all the important insights related to customers, products, orders as well as the forecasting outcomes.

Modeling time series of electricity spot prices using Deep Learning.

Using Machine Learning for time series forecasting of photovoltaic measurement for solar systems based on weather features