Github repo for my in-progress book, "Visualizing Multivariate Data and Models in R"

The House Price Prediction System is a comprehensive project aimed at predicting housing prices based on various attributes using advanced data analysis and machine learning techniques.

Code solutions for artificial intelligence labs made during my studies

In this DS project, I used Python and the Nasdaq Data Link API to analyze economic data. I cleaned financial datasets with pandas, analyzed stock trends, created visualizations with Matplotlib, and developed a linear regression model using time and expense turnover to predict a financial metric. This enhanced my skills in financial data analysis.

An single page web application to manage files, using a bit of machine learning for my academic research

Developed a user-friendly interface for individuals to track their mental fitness levels .This utilized machine learning algorithms such as linear regression model and Random Forest Regression model to analyze various inputs and detect pattern and trends.

Here we have fully implemented a number of algorithms related to machine learning

Extensive EDA providing detailed analysis of penguin dataset; ML models built to predicate penguin features for superior penguin management

Hackathon project done in 3 hours applying my Python-know-how and managing my limited team, focusing on Climate Data and Linear Regression

Computation of training set (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm (2024).

project for data science

This project uses a linear regression model to forecast stock prices. It leverages historical stock price data downloaded from Yahoo Finance to train and test the model.

Optimize linear regression parameters using a genetic algorithm. This project uses selection, crossover, and mutation to minimize the mean squared error all coded from scratch, demonstrating the application of genetic algorithms in machine learning model optimization.

The data of different types of wine sales in the 20th century is to be analysed. Both of these data are from the same company but of different wines. As an analyst in the ABC Estate Wines, you are tasked to analyse and forecast Wine Sales in the 20th century.

Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.

This repository demonstrates Python-based data mining and machine learning techniques for predicting real estate prices. It focuses on using Linear Regression as the primary model, supported by thorough Exploratory Data Analysis (EDA) and data preprocessing.

This project aims to enhance the accuracy and efficiency of stock market predictions by employing a sophisticated machine learning methodology. This project leverages the power of PySpark, a robust framework for distributed data processing, to handle large datasets and perform complex computations.

Repository related to courses and submission from kaggle

This project focuses on developing machine learning solutions for various use cases within 5G New Radio (NR) networks, specifically under the Open Radio Access Network (O-RAN) framework.