Portfolio - Machhindra Jagdale | Codebasics

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Machhindra Jagdale

Data scientist

EMAIL

[email protected]

PHONE

+91 8010099272

Download CV

About Me

Hello! I'm Naveen, a Data Scientist skilled in Machine Leaming, Python, and SOL, I love tuming complex data into clear insights that help solve real-world problems

Tools and Technologies

luse Python to handle data and create moders that eam hom

I'm good with SOL for organizing and retrieving deta

I also work with tools like Jupyter Notebooks, Pandas and Marioribanaye and show data clearly

Areas of Expertise

Building models that predict future trends and improve business decisions

Making data tasks faster and more accurate with autonation

Designing easy to understand data visualizations for better decoming

I believe in the power of learning from data and constantly improwing syoy sharing what learn and connecting with others interested in data.

1

Python Project

1

Machine Learning Project

1

Deep Learning Project

Key Skills

Machine Learning

Deep Learning

Pythone

SQL

NUmpy

Pandas

My Projects

Awards & Certificate

Python: Beginner to Advanced For Data Professionals

SQL for Data Science

Math and Statistics For AI, Data Science

Master Machine Learning for Data Science & AI: Beginner to Advanced

Deep Learning: Beginner to Advanced

Natural Language Processing

Let's Work Together!

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

EMAIL

[email protected]

Call Me

+91 8010099272

LinkedIn

https://www.linkedin.com/in/machhindra-jagdale-332aa730a?utm_source=share_via&utm_content=profile&utm_medium=member_android

GitHub

https://github.com/

Python Project

Expense Tracking System

Domain/Function: Expense Tracker

Expense Tracking System, is a simple and effective application designed to help users manage their daily expenses. It allows users to add and update expenses by entering the amount, category, date, and notes. The system categorizes spending into groups like Food, Shopping, Rent, Entertainment, and O

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Engagement

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on GitHUB

Expense Tracking System

Developed an Expense Tracking System for managing daily expenses Enabled adding, updating, and categorizing expenses Implemented analytics to track spending patterns

Expense Tracking System

Built analytics feature for expense tracking system Enabled date-wise filtering of expenses Visualized category-wise spending using charts Helped users identify major expense areas Improved financial insights and decision-making

Project Details

Expense Tracking System, is a simple and effective application designed to help users manage their daily expenses. It allows users to add and update expenses by entering the amount, category, date, and notes. The system categorizes spending into groups like Food, Shopping, Rent, Entertainment, and Others for better organization. It also provides an analytics dashboard that displays expense breakdowns and percentages by category using visual charts. This helps users understand their spending habits and make better financial decisions.

Machine Learning Project

Helth Insurance Cost Predictor

Domain/Function: Helth Insurance Predictor

A Health Insurance Cost Predictor is a machine learning–based system that estimates how much insurance premium a person will pay based on their personal and health details.

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Engagement

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on GitHUB

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on Streamlit

Helth Insurance Cost Predictor

Built a Linear Regression model using 10+ features (age, BMI, smoking, income, medical history). Performed preprocessing & feature engineering. Developed a Streamlit web app for real-time predictions with feature importance, improving interpretability.

Helth Insurance Cost Predictor

Built a Linear Regression model using 10+ features (age, BMI, smoking, income, medical history). Performed preprocessing & feature engineering. Developed a Streamlit web app for real-time predictions with feature importance, improving interpretability.

Project Details

I developed a Machine Learning-based application that estimates annual health insurance premiums based on user-specific health and demographic inputs.

🔍 Key Highlights:

Built a predictive model using Linear Regression with 10+ features such as age, BMI category, smoking status, income, and medical history
Performed data preprocessing and feature engineering to handle both numerical and categorical variables
Designed an interactive web app using Streamlit for real-time cost prediction
Implemented feature importance visualization to explain how different factors impact insurance costs
Focused on model interpretability, helping users understand how lifestyle choices influence their premiums

Deep Learning Project

Car Damege Detection

Domain/Function: Car Damege Detector

AI-powered Vehicle Damage Detection system that classifies car damage from images. Uses a CNN model to detect front & rear damage types (Breakage, Crushed, Normal). Built with Streamlit for real-time prediction, improving accuracy and faster assessment.

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Engagement

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on GitHUB

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on Streamlit

Car Damege Detection

AI-powered Vehicle Damage Detection system that analyzes car images to identify and classify damage types like dents, scratches, and breakage. Built using deep learning (CNN), it provides fast, accurate predictions through an interactive web app interface

Car Damege Detection

AI-powered Vehicle Damage Detection system that analyzes car images to identify and classify damage types like breakage, crushed areas, and normal condition using CNN, providing accurate front and rear damage detection with real-time prediction.

Project Details

I developed a Car Damage Detection system that leverages deep learning and computer vision techniques to automatically identify and classify vehicle damage from images. This project aims to simplify and speed up the inspection process for insurance claims, workshops, and vehicle owners.

🔍 Key Features:

Automatic detection of damaged areas in car images
Classification of damage types (scratch, dent, crack, etc.)
Image preprocessing and augmentation for improved accuracy
User-friendly interface for uploading and analyzing images