I build. I analyse. I ship.
Data scientist, ML engineer and full-stack developer. I turn complex problems into clean, working software — and I write about everything I learn along the way.
Six things I do well.
From full-stack development to ML pipelines and automation — clean, production-ready, and built to last.
Full-Stack Web Development
End-to-end web apps using Python, Flask, Jinja2, HTML/CSS and SQL. Secure auth, REST APIs, admin dashboards and responsive UI — all production-ready.
Machine Learning & AI
Predictive models, classifiers and neural networks with TensorFlow, Keras and scikit-learn — from data prep to deployment behind Flask APIs.
Data Science & Analysis
Clean, explore and visualise datasets with Pandas, NumPy, Matplotlib and Seaborn. Turn raw data into actionable insights and clear reports.
AI Applications & NLP
LLM-powered products — resume parsing, semantic matching, AI assistants and automation pipelines built with the OpenAI API and custom NLP.
Web Scraping & Pipelines
Extract structured data from any site with BeautifulSoup and Requests. Full pipelines that clean, transform and export to CSV, JSON or a database.
Database Design & APIs
Normalised schemas, optimised queries and RESTful APIs. Experience with MySQL, SQLite, Oracle and Flask-SQLAlchemy ORM patterns.
How deep I go, honestly.
Measured across three years of building real projects — no inflated numbers.
From problem to shipped.
Understand the problem
I start with the real problem — not just the feature request. What pain does this solve? Who uses it? What does success look like? Clear requirements save 10× the time later.
Design the architecture
Database schema, API structure, routing, folder layout — planned before a line of code. Good architecture makes features easy to add and bugs easy to find.
Build with clean code
Readable, modular, well-commented Python. Functions do one thing. No magic numbers, no spaghetti — code the next developer (or future me) can understand instantly.
Test every edge case
Empty inputs? API down? Mobile view? I test beyond the happy path — because real users always find what you didn't expect.
Ship & iterate
Deploy, gather feedback, fix what matters. A shipped imperfect product beats a perfect one that never launches. Fast iteration over endless perfection.
The stats.
Web apps, ML models, automation scripts and CLI tools
Python, TensorFlow, SQL, Data Science and more
Languages, frameworks and libraries in active use
Across LeetCode and HackerRank — SQL, DSA, Pandas
I write what I learn.
Python tricks, Flask patterns, ML concepts and developer life. Tap any post to read it right here.
From list comprehensions to context managers and decorators — the Python patterns that actually show up in real projects. Not textbook examples, real code.
Blueprints, factory pattern, config classes and folder layout — the opinionated Flask structure I use for every project, big or small.
A beginner's honest account of building a neural network — what I got wrong, what clicked, and how I went from confusion to a working model.
groupby, merge, pivot_table, apply, query — the Pandas operations that do 90% of the work in any data analysis project, with real examples.
BeautifulSoup, pagination, rate limiting, headers and data export — everything you actually need to scrape the real web, not toy examples.
No bootcamp. No paid course. Just YouTube, docs and building real things. The exact path I took from zero to shipping Flask apps.
Session management, password hashing with Werkzeug, login-required decorators — real authentication without flask-login or JWT.
How I approach every new dataset — shape checks, null handling, distribution plots, correlation heatmaps and outlier detection before any model.
Publication-quality charts, custom themes, multi-panel figures and the exact code I use to make my data visualisations actually look good.
Ready to build something intelligent?
Let's collaborate and bring your idea to life — a web app, an ML model, an automation pipeline, or something entirely new.