Detection of Skin Disease using CNN. Detects five types of disease.

Solving Sukodu puzzle in realtime using Deep Learning and Computer Vision. Display the unsolved Sudoku in front of the camera and get the instant solution projecting right on the image.

Facial Expression Recognition . Work on both Realtime as well as on a video .

Predicting & Classifying Brain tumor using CNN model

The search is over. We present to you ‘Just Try It’’ where you can select any apparel,any accessory and put it on yourself to see how it looks! Decide after trying so you get only what you really want.

This project demonstrates the working of tensorflow-extended for creating scalable ML pipelines as well to automate CI/CD pipelines.

ML Project On Bank Churn Analysis Using ANN and Hyper-parameter tuning.

feasibility and practicality of using CNNs on a Raspberry Pi for on-site plant disease detection, providing farmers with an accessible and efficient tool to manage crop health effectively.

Obesity Level Detector A machine learning model that estimates obesity levels based on user inputs, including dietary habits and physical activity. Hosted on the web, the model provides personalized health advice and recommendations.

This contains the code of Bharat Book Collection(a dummy book store for project) Back-end.

Nutrify

A machine learning model which will predict the person is normal or heart-diseased.

Machine learning project based on Linear regression

The project deals with the identification of high accuracy model among the given models to detect the cyberbullying in text by training them with the given dataset which is preprocessed and vectorized with tf-idf

Source code for Is this fake news! 🔥

The objective is to combine historical usage pattern along with the open data sources like weather data to forecast the number of vehicle booking demand in a city.

Air Qualty Prediction / PM 2.5 Forcasting ML project.

PGDBA - ML-miniproject - Telephone-Data-Churn

The Image Classifier web app swiftly identifies sports personalities like Maria Sharapova, Virat Kohli, Serena Williams, and more. Utilizing Flask, HTML, CSS, and JavaScript, this user-friendly tool allows seamless image uploading and accurate classification results.