Understand what influences bike rental usage. 🚲

Inmarsat and Rwanda Mountain Tea (RMT) Limited collaborated to test LoRaWAN IoT devices within the latter's factory premises to supplement the tea processing criteria with the main aim of producing customer desired tea grades. In this phase of the project, we deployed an IoT framework and proof of concept solution to supplement the human sensory…

Predicting consumer behaviour with ESOM and K-Means clustering. Data labelling and classification problem.

ERG3020 - Web Analytics and Intelligence Project

Spine Surgery Injury Severity (SSIS), Code for Web Analytics

Linear Regression Analysis for Bike Rental System using Excel and R

Udacity Business Analyst Nanodegree

A used car online selling company in the USA is in the process of updating their car price assessment method where they want to apply a data driven technique. The trial dataset consists of 25 variables describing 23531 car sales from 2019 to 2020. The management is very keen to apply predictive modelling for this task where the trail data set is…

The Red Apple of the Future

This repository contains all the tasks given by The Spark Foundation as part of Data Science intership program.

This predictive classification analysis will predict whether a person has heart disease or not.

Provided valuable data insights for strategic planning on furniture and home furnishings products by carrying out exploratory data analysis using Excel and PowerBI. Finally provided predictive analysis using Holt-Winters model with R programming language in well documented reports.

A repository to make basic predictions on a pharmaceutical data set, using machine learning and deep learning concepts. This is a week III project of 10 academy batch VI intensive training.

Predicting the winners of Miss Finland 2016 with penalized logistic regression, using image data.

Essential-Tech-for-Predictive-Analysis in Python

Predictive Data Analysis

This APP is meant to analyze weather data from past records and predict future weather patterns. NOTICE**SQL Not Recognized As A Programming Language On GitHub .SQL files are included**

This project predicts flight delays using machine learning. It analyzes various factors such as weather, airline data, airport congestion, and flight capacity. With an accuracy of 80%, the model provides insights into key delay causes, helping improve flight scheduling and passenger experience.

Cab Investment Strategy in the US examines market trends, customer demographics, and profitability for Pink Cab and Yellow Cab, offering insights to guide strategic investment decisions through data analysis, visualizations, and forecasting.