Analysis will help Jamboree in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.

This repository contains a Jupyter Notebook for the analysis of Non-Small Cell Lung Cancer (NSCLC) data using various machine learning techniques.

A MLR algorithm that analyzes diabetes data in African Americans to find factors predicting diagnosis

This project analyses global salary data from the AI/ML industry, encompassing various job roles, company sizes, and geographic locations. Lasso regression achieved lowest RMSE.

Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn and TensorFlow-Keras

This repository gives you access to the CLIMATEREADY survey dataset containing thermal comfort votes during the 2021 and 2022 heatwave periods in Pamplona, Spain, as well as other relevant parameters self-reported by surveyees (e.g. occupant characteristics and behaviour, key building/dwelling characteristics, sleep problems, heat-related symptoms)

An R package for modern methods for non-probability surveys

End-to-End Machine Learning project I made as a machine learning intern @ Mentorness

Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.

This project develops a machine learning model to predict the salaries of baseball players based on their past performance.

Final project for ECON434

Machine Learning Regression Model to Predict Energy Efficiency of Buildings

This repository contains predictive ml model

Feature Engineering, Regression, Classification, Model Explanation. My 2 biggest projects exploring the link between economic indicators and U.S. presidential election results.

Regression exercises and projects done at alx training

This model utilizes regression models and accurately predicts employee salaries based on experience, previous CTC, and job roles, promoting fair salary structures and optimizing resource allocation for streamlined HR operations.

Developed for my undergrad thesis, academic purposes only

Predict the energy consumed by appliances using custom-coded Machine Learning models and Algorithms like PCA, Neural Networks, Lasso, Ridge, and Linear Regression.

ML Project implementing linear, polynomial, logistic, least squares, lasso, ridge regression techniques from scratch, for classification.