Create Datasets with Hidden Images or Messages in Residual Plots

Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few y…

The goal of this project is to build multiple linear regression models for the prediction of car prices.

Multi-Linear-Reg

Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-buil…

Residual analysis in Linear regression is based on examination of graphical plots which are as follows :: 1. Residual plot against independent variable (x). 2. Residual plot against independent variable()y. 3. Standardize or studentized residual plot 4. Normal probability plot

Predicting the Likelihood of Diabetes Using Common Signs and Symptoms - About one-third of patients with diabetes do not know that they have diabetes according to the findings published by many diabetes institutes around the world. Detecting and treating diabetes patients at early stages is critical in order to keep them healthy and to ensure th…

Prediction of Miles per gallon (MPG) Using Cars Dataset

Forecast Bitcoin daily closing prices using a Python repository featuring regression and time series models. From Linear and Polynomial Regression to ARIMA, gain insights into cryptocurrency trends. Visualize historical data, evaluate models with key metrics, and analyze residuals for validation

Anomaly detection for building HVAC data.

This repository contains a project I completed for an NTU course titled CB4247 Statistics & Computational Inference to Big Data. In this project, I applied regression and machine learning techniques to predict house prices in India.

Statistical Modelling and Data Visualization of a Climate Change Dataset (January 1984 to December 2008 ) Sourced from Kaggle

To model the demand for shared bikes with the available independent variables

A MATLAB program related to Regression Models

Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Levera…

📊⚙️ Using 7 years of my sleep data, this project predicts Sleep Quality using a linear regression model based on predictors such as time in bed, time asleep, temperature, alarm, and steps.

Time Series Forecasting

The goal of the project is to predict Life Expectancy using various factors and to determine the relationship that exists between them.

Topic : Predicting Medal Counts by Countries in Upcoming Olympics Games // # Integrated historical Olympic data with demographic, health, and economic datasets to generate a large dataset # Developed a linear regression model displaying prediction accuracy close to 70%, within the margin of error

Used libraries and functions as follows: