This project involves predicting the diamond price by using Multiple Regression ML Algorithmns

Actors Image Classification Machine Learning Model using Sklearn Libraries with Aws EC2 model deployment

End-To-End project that predicts water quality as a percentage

Content Based - Movie recommender system. End-to-End project, deployed on Heroku

Text Sumamrization App using HuggingFace

This is an End to End Machine Learning Project

A ML Web App which predicts Miles Per Gallon(MPG) efficiency of a vehicle when provided 7 inputs like Weight, Displacement etc.

This repository offers a comprehensive solution for chest disease detection, covering data ingestion, preprocessing, model training, and CI/CD deployment pipelines. From raw data to automated deployment, streamline your chest disease detection process with our end-to-end solution.

Cat-Dog Classifier

Carsify is an end to end Machine learning deployed site, which uses certain features to predict the price of the car.

Containerized Web App using Docker, FastApi and Huggingface. Uses GPT2 for Text Completion.

This project involves Binary Classification problem on the sklearn breast_cancer dataset by implementation of various ML Classification Algorithms

Chest Cancer Classification using Chest CT Scan. Using Vgg16 Model.

GradeGuru is ML-powered grade predictor to forecast student exam performance. Input student information and get accurate grade predictions for proactive academic planning. Enhance student success and academic outcomes with GradeGuru.

The KKP Blood Screening Project is a web application designed for blood analysis using YOLOv5 object detection model deployed with Flask. This application allows users to upload an image and receive a labeled result indicating various blood cell types. The model is trained to detect 11 classes of blood cells

+5.5M real sales records

Industry standard machine learning project displaying modular project structure.

Analyzed a multicategory e-commerce store using big data techniques on a Kaggle dataset with the help of AWS EC2, AWS S3, PySpark, AWS Glue ETL, AWS Athena, AWS CloudFormation, AWS Lambda and Power BI!