Machine learning
Machine learning project collection
A collection of learning and internship prototypes spanning computer vision, NLP, prediction, and cloud-backed utilities.
Overview
Exploring different ways to apply machine learning
This collection brings together my earlier learning and internship prototypes. It spans animal-intrusion alerts, driver-drowsiness detection, handwriting recognition, plant-disease classification, text similarity, and question tagging.
The projects vary from notebook experiments to small applications. Together, they show how I explored different problem types and began connecting models to interfaces and services.
Technical detail
The collection covers computer vision, NLP, prediction, and application integration. Streamlit interfaces, voice utilities, MongoDB-backed tools, and S3 storage workflows appear alongside training experiments.
Each prototype has its own scope and implementation. The value of the collection is breadth of exploration rather than a single shared architecture or performance claim.