Image Processing Course - HW3

Super Resolution's the images by 3x using CNN

Implementation of different optimization algorithms. This was done as a research project for the MSc. in Computer Engineering.

Applied Multivariable Linear Regression on Iris Dataset

Creating a simple sample data and than calculating Mean Squared Error using both numpy and sklearn.

This Repository contains scratch implementations of the famous metrics used to evaluate machine learning models.

Templates of statistical and DL forecasting on some synthetic data and lastly predicting sunspot using kaggle sunspot dataset.

Regression - Bulldozer Sales Price - Kaggle Competition

Value to Business :: Using this Regression model, the decision-makers will able to understand the properties of various products and stores which play an important and key role in optimizing the Marketing efforts and results in increased sales.

Program for non-planar camera calibration, mean square error, RANSAC algorithm, and testing with & without noisy data using extracted 3D world and 2D image feature points.

Performing gradient descent for calculating slope and intercept of linear regression using sum square residual or mean square error loss function.

Classifying whether the credit card transaction is fraudulent or not using Logistic Regression

Python images vector quantizer lossy compressor and decompressor.

This project was to predict where COVID hotspots would show up around the country with the Delta variant at play. I used infection rate as my dependent (labeled) variable. My goal was to identify county-level characteristics that would point to future outbreaks, so feature level importance was an important consideration.