Portfolio

Building practical AI/ML prototypes with clear demos.

I focus on applied machine learning, computer vision, and learning-based systems. I enjoy turning ideas into working prototypes and documenting what I learn.

Machine LearningComputer VisionReinforcement LearningPython
About

Short, specific, and focused.

I am an engineering student exploring AI/ML and RL through hands-on builds. I prefer learning by shipping: small products, experiments, and technical guides.

What I am good at

  • Building end-to-end ML demos (data + model + simple UI)
  • Computer vision experiments using OpenCV
  • Writing clear technical documentation that others can follow

What I am currently learning

  • Better evaluation and reproducibility for ML experiments
  • System design basics for deploying ML services
Work

Featured projects

A small set of projects that demonstrate how I build, document, and ship. Each card links to a live demo or repository.

Screenshot of WhatsApp Chat Analyzer : AI-Powered Data Analytics

WhatsApp Chat Analyzer :
AI-Powered Data Analytics

A robust Streamlit application built to extract conversational insights through traditional exploratory data analysis, combining dynamic visualizations with the Gemini API for deep personality and behavior analysis.

PythonPandasMatplotlibSeabornStreamlitWordCloudGemini API
Screenshot of Movie Recommender System app

Movie Recommender System

A recommendation demo that suggests similar movies. Built to practice NLP-style feature extraction and user-facing ML delivery.

PythonStreamlitPandasNumpySeabornSci-kit learn
Screenshot of EcoSync - Full-Stack Sustainability Platform

EcoSync - Full-Stack Sustainability Platform

A collaborative web application built under hackathon constraints, designed to incentivize eco-friendly actions through a verified credit system and community-driven engagement.
Note:Currently backend is shutdown so website will not work

FrontendBackendAI Server
Screenshot of CodeType: a frontend coding practice website

CodeType - Frontend Coding Practice

A lightweight practice website built to explore UI/UX and quick iteration ("vibe coding" exploration) with a clean interface.

FrontendUI PracticeGitHub Pages
Thumbnail for Lenovo TB-X306X rooting guide

Lenovo TB-X306X Rooting Guide

A step-by-step technical guide published on GitHub and shared to the community (XDA). Focused on clarity and reproducibility.

Technical WritingAndroidCommunity
Client Work

Freelance & client projects

Real-world solutions built for clients with practical business use cases.

Android screenshot of Swadisht Mess mobile web application

Swadisht Mess Web Application

Designed and delivered a custom mobile-first web application for Swadisht Mess, optimized specifically for Android users to strengthen digital presence, improve customer interaction, enable seamless menu access, and streamline daily service workflow. Developed as a real client project with production-focused thinking, practical usability, and business impact in mind.

Mobile FirstClient ProjectWeb AppFull Stack
Writing

Technical articles

I write to clarify concepts and document progress. This is also where I share broader research summaries.

Blog cover image related to NLP history

The NLP landscape (1960s - 2020s)

A high-level timeline of NLP milestones, from early statistical methods to modern transformer-era systems.

NLPHistoryMedium
Research

Research paper & poster presentation

A first-semester research experience focused on abuse detection using a hybrid heuristic–machine learning approach, later presented as a poster.

Android screenshot of Swadisht Mess mobile web application

A Hybrid Heuristic–Machine Learning Approach for Abuse Detection

Submitted under the guidance of Sundeep Deulkar Sir and presented as a poster at CTFC 2025. The work explores slang normalization, TF-IDF features, and machine learning for abuse detection.

Machine LearningNLPResearch
Tooling

Skills and tools

I keep the stack lean and practical. I focus on fundamentals, reproducible experiments, and clear demos.

Core
PythonNumPyPandasscikit-learn
Visualization & Analysis
MatplotlibSeaborn
Computer Vision
OpenCV
Web / Deployment (intermediate)
FastapiReact.jsStreamlitGitHub Pages
Other
C lnaguage
Direction

Long-term interests

I am particularly interested in reinforcement learning and agentic systems - how agents learn from interaction, how we evaluate them, and how we build reliable behavior under constraints.

Why RL?

RL is a practical way to study learning-by-doing. It connects perception, decision-making, and feedback loops, which makes it a strong foundation for building intelligent systems beyond static prediction.

What I want to explore next

  • Small agents in simulated environments (clear reward design)
  • Better evaluation for agent behavior (robustness, safety, generalization)
  • Bridging ML prototypes to deployable services
Contact

Let us connect

Best way to reach me is via LinkedIn.

Direct links

Email: vedantkawade.official@gmail.com
GitHub, LinkedIn, and X are linked below.