Hi, I'm Rohit Bedse

Machine Learning & NLP Focused Computer Engineering Student

I design and implement end-to-end machine learning systems — from data preprocessing and feature engineering to modeling, evaluation, and basic deployment.

🚀 Core Focus

• Building end-to-end ML pipelines
• Designing NLP systems for real-world text data
• Applying statistical thinking to model development
• Writing modular, structured, production-oriented code

🧠 Featured Projects

💬 YouTube Comment Analyzer (NLP System)

Chrome Extension + Backend ML Pipeline

• Built a real-time comment analysis system for YouTube
• Designed preprocessing pipeline for multilingual input
• Implemented sentiment classification (Positive / Neutral / Negative)
• Created visualization layer for audience sentiment insights
• Integrated frontend extension with backend API

Tech: Python, scikit-learn, NLP, Flask, JavaScript

🛒 Amazon ML Challenge – Multi-Modal Price Prediction

Text + Image Based ML System

• Built a multi-modal pipeline combining textual and image features
• Extracted text features using TF-IDF and embeddings
• Processed image data for feature extraction
• Trained regression models for price prediction
• Evaluated model performance using appropriate regression metrics

Tech: Python, scikit-learn, NLP, Computer Vision basics

🎬 Content-Based Movie Recommendation System

• Designed a recommendation engine using TF-IDF + cosine similarity
• Processed movie metadata (overview, genres, tagline)
• Generated similarity matrix for content-based filtering
• Built a reusable recommendation function

Tech: Python, pandas, scikit-learn

📊 Exploratory Data Analysis Projects

• Performed EDA on real-world datasets (insurance, startup funding, etc.)
• Identified feature relationships and data quality issues
• Applied visualization techniques to derive actionable insights

Tech: pandas, NumPy, Matplotlib / Plotly

🛠️ Technical Skills

Languages & Libraries

Python, pandas, NumPy, scikit-learn

Machine Learning

Regression, Classification, Model Evaluation, Feature Engineering

NLP

Text preprocessing, TF-IDF, Sentiment Analysis, Similarity Systems

Tools & Backend

Flask, Streamlit, Git, GitHub, Jupyter Notebook

🏗️ Engineering Approach

• Focus on understanding algorithms beyond surface-level usage
• Emphasis on clean project structure and reproducibility
• Implement concepts from scratch to build intuition
• Continuously improving deployment and system design skills

📌 Currently Expanding Into

• Retrieval-Augmented Generation (RAG) systems
• FastAPI-based ML model deployment
• LLM workflows and structured outputs
• Improving mathematical depth behind ML algorithms

🎯 Objective

To contribute to impactful machine learning projects where I can apply strong fundamentals, structured thinking, and practical implementation skills.

🤝 Connect

📄 Resume
https://raw.githubusercontent.com/rohitbedse/rohitbedse/main/rohit_bedse1.docx

🔗 LinkedIn
https://www.linkedin.com/in/rohit-bedse-086b86262