Data science and machine learning

Anuj Kulkarni

Turning messy data into something insightful

I build focused ML systems, analysis tools, and experiments that move from notebook to deployment while maintaining clarity.

GitHub LinkedIn Resume
Technical Blog Featured

Brewing the Perfect Model with Chai

Grid Search CV explained through the art of making chai. A small, practical walkthrough of hyperparameter tuning with code examples.

Jul 21, 2025 5 min read
Read on Medium

Stack

The tools I actually reach for

Languages

Core implementation stack.

Python JavaScript TypeScript HTML/CSS

ML & Data

Modeling, feature work, and analysis.

Scikit-Learn Pandas NumPy

Visualization

Communication through charts and notebooks.

Matplotlib Plotly Seaborn Jupyter

Tools

Environment and delivery.

Git GitHub VS Code Docker

Projects

Selected work

Intel Sensors

ML

Room Occupancy Prediction using Random Forest (Supervised) + K-Means (Unsupervised) on real Intel sensor data.

Python Scikit-Learn Random Forest
Live Demo GitHub Repo

House Price Prediction

Regression

House Price Prediction with multivariate Linear Regression (ElasticNet) and interactive website.

Python ElasticNet Web Interface
Live Demo GitHub Repo

Spotify

Clustering

Music Clustering on a large Spotify dataset (1.2M+ tracks) using unsupervised learning techniques.

Python Clustering Large-Scale Data
GitHub Repo

Rating Converter

Tool

CodeChef ↔ Codeforces Rating Converter using Linear Regression with web interface.

Python Linear Regression Web App
Live Demo GitHub Repo