This project is a Streamlit application designed to perform image classification using two powerful machine learning models: MobileNetV2 and a custom CIFAR-10 model. The application allows users to upload images and receive predictions along with confidence scores.

During my 6-week virtual internship with Motioncut, I created a sleek, animated login page using HTML, CSS, and media queries. This frontend project was designed to be visually engaging and responsive, serving as the foundation for a more extensive web application I plan to develop in the future.

I have this repo various project as task for internship

Predict electric vehicle (EV) growth over 3 years using real-world data and machine learning. The model learns adoption patterns from historical EV data. Results are shown in an interactive Streamlit dashboard. Includes county-wise comparison, forecasts, and clean visualizations.

Secure Data Hiding in Images Using Steganography

Week 1 Task of Exhaustive analysis of Indian Agriculture using Power BI.

My submission for the Salesforce Developer intern program cohort 5 conducted by TheSmartBridge.

Netflix Dataset Analysis – AICTE Internship Major Project (Oct 2025)

As part of an AICTE internship, this NLP-powered chatbot leverages Python, Streamlit, and Scikit-learn to answer cryptocurrency queries and fetch live prices for the top 20 coins using the CoinGecko API. Combining TF-IDF vectorization and Logistic Regression, it offers an interactive web interface for real-time crypto insights.

A simple stopwatch app built with Jetpack Compose