Naitik.
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Open to internships & collaboration

Naitik Patidar — Data Science & AI/ML Student

AI/ML • Data Science • Research

I am a Data Science student at IIT Madras, diving deep into the mechanics of Artificial Intelligence and Machine Learning. I build technical projects that put theory into practice—using Python and Data Analytics to extract insights, and Generative AI to push the boundaries of what models can do.

With a strong interest in AI research and tech entrepreneurship, I am open to connecting with fellow builders, researchers, and anyone working at the intersection of data and intelligent systems.

View Projects About
7+
Projects Built
200+
Participants in Hackathon that we Organized
13+
Certifications
Python Machine Learning Deep Learning Data Science SQL NumPy Pandas Scikit-Learn Streamlit Generative AI Agentic AI Data Analytics C++ Digital Marketing Project Management Git Python Machine Learning Deep Learning Data Science SQL NumPy Pandas Scikit-Learn Streamlit Generative AI Agentic AI Data Analytics C++ Digital Marketing Project Management Git

Selected Work

Projects

ML Placement Predictor

End-to-end ML web app using Streamlit + Logistic Regression, achieving 84.7% accuracy predicting placement from CGPA/IQ.

PythonStreamlitScikit-LearnLogistic Regression
View ML Placement Predictor project →

OtakuAnalytics: Filtering the Masterpieces

EDA + feature engineering pipeline on 12,000+ anime entries, filtering statistical outliers to surface acclaimed titles.

PythonPandasMatplotlibEDA
View OtakuAnalytics: Filtering the Masterpieces project →

E-commerce Sales Analysis

EDA on a 5,000-order dataset (~₹20.67M revenue), surfacing top regions, categories, and high-value customer patterns.

PythonPandasSeabornData Analytics
View E-commerce Sales Analysis project →

AI Impact on Students

Analysis of GenAI usage vs academic performance across 50,000 records.

PythonPandasData AnalysisVisualization
View AI Impact on Students project →
Explore my Machine Learning & Data Science Projects →

Journal

Recent Writing

Supervised vs Unsupervised Learning: What's the Difference?

Learn the difference between supervised and unsupervised learning, how each method works, common algorithms, examples, advantages, limitations and when to use them.

Read: Supervised vs Unsupervised Learning: What's the Difference? →

What Is Machine Learning? A Beginner's Guide

Learn what machine learning is, how it works, its main types, common algorithms, real-world applications, and how to start learning machine learning with Python.

Read: What Is Machine Learning? A Beginner's Guide →

How to Train Neural Networks: A Practical Guide for Beginners

A step-by-step breakdown of how neural networks actually learn—covering prediction, loss, gradients, and parameter updates.

Read: How to Train Neural Networks: A Practical Guide for Beginners →
Read my AI, ML & Data Science Blog →

Let's connect

Interested in working together, have a question, or just want to say hello?

Get in Touch GitHub