Weather prediction linear model built with R and data analysis techniques.

This project is to build an ARIMA model to predict supermarket deals (Coles and Woolworths). It is written in R programming language. The dataset consists of multiple attributes such as date and items name showed on website. The price are updated progressively. The dataset is not having all items, instead only the items of interest.

Shiny test

Code used in the paper "A Blood-Test Based Predictive Model for the Cognitive Decline in Probable Alzheimer’s Disease Patients"

Airline customer satisfaction prediction & analysis

This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.

Analyzing the correlation between nitrogen uptake and remotely sensed vegetation indices

Classification data mining base on naive bayes Algorithm for predicting employee tardiness

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…

Data science projects with R programming language

Explore and Predict Housing Sales Price in Ames, IA

R package frost: prediction of minimum temperature for frost forecasting in agriculture

This repository is about my first GRIP (Graduate Rotational Internship Program) task at The Sparks Foundation. The task is about prediction using the supervised machine learning technique in the R program.

Regression models for predicting bitcoin price

Reproduce results from the paper "Combining randomized and non-randomized data to predict heterogeneous effects of competing treatments."

Machine learning model implemented to accurately predict the housing prices in Boston suburbs.

This repo hosts an Aquaculture Data Project focused on supervised learning experiments for both classification and regression tasks. Utilizing the 'escapesClean.csv' dataset, models such as Logistic Regression and Random Forest Regressor are built. An R Shiny app for real-time predictions is also included for model deployment.

Bayesian prediction of NFL scores

This is a prediction model that predicts the future values of the particular parameter based on the history of the parameter in the dataset used. This is programmed using R programming language.

How to deploy previous 'randomForest' ML model as a 'Shiny' web application