Overview
Technical skills
Projects
Roles

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Overview

AI and machine learning focused Computer Science undergraduate with practical coursework and projects in data preprocessing, exploratory analysis, and model training. Completed structured ML training and built projects covering clustering-based segmentation, multi-dataset classification, and data visualization. Skilled with Python-based data workflows and common ML/data science libraries.
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Technical skills

Languages
6
C++
Python
SQL
JavaScript
Node JS
C
AI/ML
6
Computer Vision
NumPy
Pandas
Scikit-learn
Google Colab
Gradio
Other
9
MySQL
Oracle
Matplotlib
GitHub
Git
Linux
AI Agents
Jupyter Notebook
Machine Learning

Projects

Data Analysis & Visualization
Performed data cleaning, manipulation, and validation using Pandas and NumPy. Created visualizations with Matplotlib to inspect trends and patterns in datasets. Organized analysis steps to support downstream modeling and reporting.
Machine Learning Classification Projects
Implemented and compared multiple classification models on several problem domains including customer prediction, student results, credit risk, and medical datasets. Performed data preprocessing before training, then evaluated models using classification metrics and confusion matrices. Used results to assess which algorithms performed best per dataset.
Customer Segmentation using Machine Learning
Built a customer segmentation workflow using cleaned and standardized customer data. Applied feature reduction with PCA and used K-Means clustering to group customers into segments. Focused on removing non-informative identifiers and preparing numerical features for modeling.