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Achievement: Pull SharkAchievement: YOLO

Achievements

Achievement: Pull SharkAchievement: YOLO

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BPSKartik/README.md

Kartik Chaturvedi

BCA in Artificial Intelligence · Bennett University

Open to internships

Email Live demo

I'm a BCA (Artificial Intelligence) student at Bennett University. I learn by building real projects — web apps, bots, and small tools — and I'm now going deeper into AI / ML. Looking for an internship where I can learn from a team and contribute.

kartik@dev:~$ whoami
> BCA (Artificial Intelligence) student · Bennett University
> I learn by building: web apps, bots, small tools
> Now focused on AI/ML — and shipping code on GitHub regularly

🧰 Tools & languages I've used
Languages Python · JavaScript · TypeScript · Java · SQL
Web Next.js · React · Node.js · Tailwind CSS · Prisma
AI Anthropic Claude API · LLM app basics · prompt & context engineering
Tools Git · Docker · Linux · PostgreSQL · Vercel
tools and languages

🚀 Things I've built

Project What it is What it shows
Vibzy A social web app I built myself — feed, stories, reels, DMs, passkey login, realtime notifications. Building a full app · auth · realtime · databases
AI study bot A Discord bot that answers coursework questions and makes PDF notes, using the Claude API with channel context. Applied AI / LLM · Node.js · API integration
Self-hosted stack My own Linux home server — Docker services, Cloudflare tunnels, a Postgres DB, a game server behind it. Linux · Docker · networking · running things reliably
Minecraft plugin A custom Java plugin for my server — commands, events, and Discord webhooks. Java / OOP · event-driven code

📚 What I'm learning now

  • Machine learning & deep-learning fundamentals in Python (my BCA AI focus)
  • Writing tests and thinking about design earlier in a project

If I can implement it from scratch, I actually understand it. I push what I learn as I go:

Repo What's in it
ml-from-scratch Classic ML algorithms written in pure NumPy — linear/logistic regression, kNN, k-means, and an MLP with hand-written backprop
ml-journey My ML notes as runnable scripts — NumPy/pandas, regression, classification
sms-spam-detector End-to-end ML mini-project: TF-IDF + Naive Bayes, train & predict
dsa-python Data structures & algorithms with complexity notes and pytest tests

📊 GitHub activity

GitHub stats streak

📫 Reach me

  • Email — kartik@xeta.in
  • Happy to talk about a role, a project, or just code.

Popular repositories Loading

  1. justify justify Public

    Every line earns its place — finds code that cannot justify its existence, splits it AI vs human, and removes it only with proof. CLI, GitHub Action and MCP server.

    Python 1

  2. zeta-api zeta-api Public

  3. ml-from-scratch ml-from-scratch Public

    Classic ML algorithms implemented from scratch in pure NumPy — linear/logistic regression, kNN, k-means, and an MLP with hand-written backprop.

    Python 1

  4. BPSKartik BPSKartik Public

    Profile README

  5. xora-brand xora-brand Public

    Official Xora brand assets — logos, colors, and usage guidelines.

  6. vibzy-brand vibzy-brand Public

    Official Vibzy brand assets — logos, colors, and usage guidelines.