Add Helping Hand career navigator app (frontend, backend, ML engine, and data)

[Raheel-glicth]

Motivation

• Provide a simple, self-contained career guidance web app that uses a small custom ML distribution engine and LLM-backed narrative to recommend tech career paths and surface curated learning roadmaps.

Description

• Add a static frontend under public with index.html, style.css, and app.js implementing a 12-question diagnostic, progress UI, result rendering, resource submission form, and API interactions.
• Implement a minimal Node.js HTTP server in server.js that trains a lightweight multi-output logistic model from data/training-data.json, exposes GET /api/fields, POST /api/recommend, and POST /api/resources, and persists submissions and resources to JSON files.
• Add data fixtures data/resources.json, data/training-data.json, and an initially empty data/submissions.json to seed roadmaps, training samples, and storage.
• Add package.json with start/dev/lint scripts and a top-level README.md documenting usage and environment variables.

Testing

• Ran the lint script npm run lint which executes node --check server.js and node --check public/app.js and reported no syntax errors.
• Performed a basic smoke start with npm start and verified the server serves index.html and responds to GET /api/fields and POST /api/recommend for a valid payload (smoke checks succeeded).

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Codex Task

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