Practice Assignments for Data Science Coursework

"This repository contains implementations of Boosting method, popular techniques in Model Ensembles, aimed at improving predictive performance by combining multiple models. by using titanic database."

Using R Markdown for Data Analysis, Machine Learning

This repository contains my coursework (assignments, semester exams & project) for the Statistical Machine Learning course at IIIT Delhi in Winter 2024.

This project employs ensemble learning methods to forecast cybercrime rates, utilizing datasets with population, internet subscriptions, and crime incidents. By analyzing trends and employing metrics like R2 Score and Mean Squared Error, it aims to enhance prediction accuracy and provide insights for effective prevention strategies.

Analisis KNN, Random Forest dan Boosting Algorithm.

Boosting Functional Regression Models. The current release version can be found on CRAN (http://cran.r-project.org/package=FDboost).

A project to predict scores of students based on 7 parameters. Created a Flask App and then converted to a Docker Image. Hostel Online to demonstrate implementation of CI/CD pipelines on AWS EC2

Machine Learning for High Energy Physics.

Forward stagewise sparse regression estimation implemented for gretl.

A simulation study completed during a visit at the Microsoft Research, Cambridge (May-Sept, 2022)

Machine Learning course, Python.

Flight Price Prediction using Advance Machine learning

Прогнозирование оттока пользователей (Проект в skillbox)

Predictive Modeling and Clustering Insights for Success on Shark Tank

ML | Regression Analysis| Random Forest| XGBoost| Gradient Boost| EDA| Feature Engineering| Feature selection

Improving previous trainings with boosting algorithms