Portfolio - Ankit Vishwakarma

Ankit Vishwakarma

Data Aspirant

Resume

1

SQL Project

2

Machine Learning Projects

About Me

I’m Ankit, currently learning and growing in the field of data science.
I love working with data to find patterns, make predictions, and solve meaningful problems.
This website is a reflection of my progress — from beginner experiments to more polished projects.
Thanks for visiting, and I’d love to hear your feedback or connect!

Key Skills

Python

C++

Generative AI

Classical ML

Computer Vision

Recurrent Neural Networks

My Projects

Expense Management System

Domain/Function: Personal Finance

Credit Risk Model

Domain/Function: Finance

Insurance Premium Prediction

Domain/Function: Healthcare

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

Let's Connect

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.

Download Resume

Resume

Mail Me

[email protected]

https://www.linkedin.com/in/ankit-vishwakarma-500a7b324/

Call Me

+91 8581076921

GitHub

https://github.com/ankit85810

SQL Project

Expense Management System

Domain/Function: Personal Finance

An Expense Management System built using Streamlit for the frontend and FastAPI for the backend. This application helps users efficiently manage and track their expenses with an intuitive interface and real-time updates.

View Project
on GitHUB

This interface is designed for adding and updating daily expenses.

This UI allows you to analyze how expenses are distributed across categories.

Project Details

Expense Management System is a simple and easy-to-use web application that helps you keep track of your spending. With this tool, you can add, edit, and delete your expenses, organize them by category, and view summaries with helpful charts. The app uses Streamlit for a friendly interface and FastAPI for fast, reliable data handling. It’s perfect for anyone who wants to manage their finances better and see where their money goes. Just install the app, enter your expenses, and start gaining insights into your spending habits!

Machine Learning Project

Credit Risk Model

Domain/Function: Finance

This is a Streamlit-based web application for predicting the credit default risk of a loan applicant using various financial and personal parameters. The app calculates the default probability, assigns a credit score, and categorizes the result into a rating (Poor, Average, Good, Excellent).

View Project
on GitHUB

View Project
on Website

Credit risk model

Project Details

Credit Risk Modeling App is a user-friendly web application built with Streamlit that predicts the likelihood of a loan applicant defaulting on their loan. By entering financial and personal details-such as income, loan amount, and credit history-the app instantly calculates the probability of default, assigns a credit score (ranging from 300 to 900), and provides a risk rating (Poor, Average, Good, or Excellent). The app uses a pre-trained machine learning model stored in a .joblib file to process inputs and generate predictions in real time. It is ideal for lenders and analysts who want quick, data-driven insights into an applicant’s creditworthiness. The project is easy to set up, requiring only a few commands to install dependencies and launch the app, making credit risk assessment accessible and efficient for everyone.

Machine Learning Project

Insurance Premium Prediction

Domain/Function: Healthcare

This application uses machine learning models to estimate health insurance premiums based on various factors including age, income, medical history, lifestyle choices, and more.

View Project
on GitHUB

View Project
on Website

age < 25

age >= 25

Project Details

Insurance Premium Predictor is a machine learning-powered web application that estimates health insurance premiums based on your personal, medical, and lifestyle information. With a simple and intuitive Streamlit interface, users can enter details like age, income, medical history, BMI, smoking status, and more to receive a personalized premium prediction in seconds.

The app uses specialized models for young adults (25 years or younger) and older adults, ensuring more accurate and age-appropriate estimates. Behind the scenes, your inputs are processed, transformed, and routed to the right machine learning model, which then calculates your likely insurance premium. The system considers over a dozen factors, including demographics, health indicators, financial status, and genetic risk, to provide a comprehensive and tailored prediction.