How ayushbadwaik/mltlab-cm23051 works
This repository is a collection of practical lab exercises, not one unified application. The clearest runtime workflows are PostLab’s HTTP-based AI resume-builder backend and Prac2’s hand-drawn digit recognition. Other practicals include HTML pages and datasets or model assets, but their behavior is not established by the sampled source; those components are shown without inferred wiring.
Main entry points: server.js HTTP server · air.py Gesture drawing and prediction · index.html Resume page · Ayush_digit_model.h5 Digit model
Components 17
AI Resume Builder
- HTTP server
PostLab/server.js - Resume page
PostLab/index.html
Air Canvas
- Gesture drawing and prediction
Prac2/air.py - Digit model
Prac2/Ayush_digit_model.h5 - Drawing canvas
Other Practicals
- Exercise pages
- Prac1 page
Prac1/index.html - Prac3 page
Prac3/index.html - Prac4 page
Prac4/index.html - Prac5 page
Prac5/index.html - Prac6 page
Prac6/index.html - Prac7 page
Prac7/index.html - Prac8 page
- Prelab page
Prelab/index.html
Other components
- User
- Groq API
- Camera
Connections 14
- User → HTTP server: requests page
- HTTP server → Resume page: reads file
- HTTP server → Groq API: forwards chat request
- Camera → Gesture drawing and prediction: provides frames
- Gesture drawing and prediction → Digit model: loads model
- Gesture drawing and prediction → Drawing canvas: draws and predicts
- User → Prac1 page: opens
- User → Prac3 page: opens
- User → Prac4 page: opens
- User → Prac5 page: opens
- User → Prac6 page: opens
- User → Prac7 page: opens
- User → Prac8 page: opens
- User → Prelab page: opens