The project deals with determining and predicting the type of accident taking place in the city of Austin. The data would help in understanding what possible factors are leading to the accidents based on the severity of the incident that has occurred.

This repository provides a practical, data-centric AI/ML module for biomedical researchers. It covers R programming, data preparation, model building, and AI/ML applications using AWS SageMaker and Jupyter notebooks.

ML Interview Questions, Coding Tasks

This project is to build a model that *predicts the human activities* such as __Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing__ and __Laying__ as done in Smart-Watches.

Artificial Intelligence Virtual Experience Program

🚗 Engineered a high-performing car price prediction model, empowering informed decisions in the dynamic car market. 🚘💰

Sentiment Analysis on Amazon Fine Food Reviews

It is an search engine designed for Ex-servicemen , which empower ex-servicemen in their transition from military service to civilian employment.

An image classifier built using Support Vector Machine (SVM) to distinguish between three categories of images. Deployed via an interactive Streamlit web application.

Learning to training a LLM model

Stroke Prediction using Machine Learning

This ML project predicts oil spills using various machine learning algorithms like XGBoost and Random Forest. This project also contains saving and load of the model to make predictions on a sample dataset.

Student 360 deals with analyzing the student performance based on the various external factors to determine the student dropout rate and predict the CGPA of the students.

This project uses machine learning to predict Turbine Energy Yield (TEY) from gas turbine data, optimizing settings to improve energy output, reduce fuel consumption, and cut costs. TEY predictions help detect deviations from normal operations, signaling potential turbine issues like degradation.

Customer churn is a significant issue for big business companies. Companies are attempting to create methods for predicting customer churn to get a direct impact on getting more revenues, particularly in telecom companies.

Implementation of multiple projects related to Predictive Analytics.

Academic project of BDA(Big Data Analytics) Predictive modeling and anomaly detection on Bitcoin time-series data using Python. Includes data cleaning, feature engineering, and regression-based forecasting with Linear Regression, Random Forest, and XGBoost models.

👩🏻‍🍳🍽️Restaurant Success Prediction using ML

This repository contains the code and resources for a comprehensive machine learning project focused on forecasting the prices of pre-owned vehicles. Exploring a diverse dataset encompassing crucial car attributes such as year, mileage, fuel type, transmission, and more.

A series of six hands-on projects completed during my PGP ML and AI academic training with UT Austin and Great Learning