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nandan-byte/README.md
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B. Deshamukh

CS Engineer · ML Systems · Backend · Data Science

Portfolio LinkedIn Gmail Location


About

Final-year Computer Science & Engineering student at AJIET (CGPA: 8.24) building production-ready systems at the intersection of machine learning, backend engineering, and data science.

I work across the full ML lifecycle — from raw data and model training to inference APIs and deployed web apps. My projects span RAG systems, CNN-based computer vision, ensemble ML models, and real-time Java applications.

Current focus: LLMs · Computer Vision · REST APIs · Data Pipelines

Tech Stack

Languages

Python Java SQL JavaScript HTML5 CSS3

ML / Data Science

TensorFlow Scikit-learn Pandas NumPy LangChain Power BI

Backend & Deployment

FastAPI Streamlit Docker Supabase MySQL

Tools

Git GitHub VS Code Jupyter Google Colab


Featured Projects

🧠 Multimodal Document Intelligence System

Python · LangChain · FAISS · Google Gemini

RAG-powered document Q&A system with full multimodal support. Converts PDFs and text into vector embeddings via FAISS for semantic retrieval, grounded to source documents.

  • Built end-to-end document ingestion, chunking, and embedding pipeline
  • Integrated Google Gemini for contextual question answering
  • Web-based frontend for document upload and conversational querying

GitHub


🌾 AgriSense — AI Crop Advisory System

Python · Scikit-learn · XGBoost · LightGBM · CatBoost · FastAPI · Supabase

District-specific crop recommendation engine trained on 24,500+ rows of Karnataka agricultural data.

  • Ensemble of Random Forest, XGBoost, LightGBM, CatBoost, ExtraTrees → 89% accuracy
  • FastAPI inference API with prediction logging in Supabase (PostgreSQL)
  • Designed for real-world agricultural decision support

GitHub


🌿 Plant Disease Recognition System

Python · TensorFlow · CNN · Streamlit

CNN-based image classifier for 38 plant diseases trained on 87,000 labeled leaf images.

  • Applied normalization, resizing, and augmentation for robust generalization
  • Deployed as a live Streamlit web app for real-time inference from leaf photos

GitHub Live Demo


❤️ Heart Disease Risk Prediction & Analysis

Python · Pandas · Scikit-learn · Power BI

EDA and ML pipeline on 918 clinical records for heart disease risk identification.

  • Trained Logistic Regression, Decision Tree, SVM, Naive Bayes, KNN → 86% accuracy
  • Built Power BI dashboard visualizing risk across age, gender, and cholesterol levels

GitHub Live Demo


💬 Java Client–Server Chat Application

Java · Swing · Sockets

Real-time chat application with custom client–server architecture using Java Sockets.

  • Built with ServerSocket/Socket APIs and DataInputStream/DataOutputStream
  • Dynamic UI with auto-scrolling chat via Swing components and multithreading

📊 Sorting Algorithm Visualizer

Java · Swing

Interactive visualizer demonstrating sorting algorithm behavior in real time.

  • Bubble Sort animations with controlled repaint cycles and custom rendering
  • Multithreaded comparisons and swaps to illustrate time complexity live

Certifications

Certification Issuer Year
AI & Data Analytics Internship Edunet Foundation (AICTE & Shell India) 2025
Python Programming Infosys Springboard 2025
AI Foundations Associate Oracle Cloud Infrastructure 2025
Programming in Java NPTEL 2024

GitHub Stats


Building systems that turn data into decisions.

Pinned Loading

  1. AgriSense-AI-Crop-Advisory-System AgriSense-AI-Crop-Advisory-System Public

    Jupyter Notebook 1

  2. Deep-Learning-for-Battery-State-of-Health-SoH- Deep-Learning-for-Battery-State-of-Health-SoH- Public

    Jupyter Notebook

  3. Heart-Disease-Risk-Prediction-and-Analysis- Heart-Disease-Risk-Prediction-and-Analysis- Public

    Jupyter Notebook

  4. Plant-Disease-Recognition-System Plant-Disease-Recognition-System Public

    A deep learning–based web application that detects plant diseases from leaf images using a trained CNN model. Built with TensorFlow and Streamlit, it allows users to upload plant images and receive…

    Jupyter Notebook

  5. Document-QA-System-using-RAG Document-QA-System-using-RAG Public

    Python

  6. End-to-End-Wine-Quality-Prediction End-to-End-Wine-Quality-Prediction Public

    CSS