Artificial Intelligence Virtual Experience Program

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 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.

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.

Sentiment Analysis on Amazon Fine Food Reviews

ML Interview Questions, Coding Tasks

Stroke Prediction using Machine Learning

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.

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

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

👩🏻‍🍳🍽️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.

Implementation of multiple projects related to Predictive Analytics.

The project deals with predicting the number of persons killed based on the contributing factors such that necessary precautions and actions can be taken in order to avoid the accidents and reduce the death rates and injuries of the person in the New York city.

🚗 Engineered a high-performing car price prediction model, empowering informed decisions by Identifying the key features that most influence car prices in the market. 🚘💰

PySpark is a Python API for support Python with Spark. Whether it is to perform computations on large datasets or to just analyze them

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.

🔍 This repo focuses on detecting Parkinson's Disease using machine learning techniques on vocal features. The project includes data preprocessing, analysis, and model training, achieving a remarkable 99.6% accuracy with the Random Forest Classifier. 🧠

SalifortMotorsHRAnalytics repository showcases Data Analytics, Visualization, Python, Statistics, and ML skills. It contains markdown file, pickle files for models, and an executive summary. To run the markdown file, adjust the path variable for pickle files and comment out fitting and saving codes.

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.