Abdul Rehman

Artificial Intelligence Undergraduate | Machine Learning | Deep Learning | NLP | Data Science

hello.arehmanmughal@gmail.com +92 316 7211435 Sialkot, Pakistan

Professional Summary

Artificial Intelligence undergraduate focused on Machine Learning, Deep Learning, Natural Language Processing, Data Science, and cloud-based applications. Experienced in developing project-based solutions using Python, including predictive modeling, sentiment analysis, RAG applications, exploratory data analysis, and Streamlit-based deployment.

Education

Bachelor of Artificial Intelligence 2023 – Present

University of Management and Technology (UMT), Sialkot

Relevant Coursework: Machine Learning, Deep Learning, Natural Language Processing, Data Science, Data Structures & Algorithms

Technical Skills

Programming

Python SQL

Machine Learning

Machine Learning Scikit-learn Predictive Modeling

Deep Learning

Deep Learning TensorFlow Artificial Neural Networks

NLP

NLP NLTK Hugging Face Transformers RAG

Data Science

Pandas NumPy Matplotlib Seaborn Data Analysis

Tools & Deployment

Jupyter Git GitHub Streamlit AWS

Selected Projects

Customer Churn Prediction

GitHub Live Demo

Python • Pandas • NumPy • Scikit-learn • Joblib • Streamlit

Developed a machine learning application to estimate customer churn likelihood from customer, service, contract, and billing information.
Built and deployed the prediction application using Scikit-learn, Joblib, and Streamlit.

Sentiment Analysis System

GitHub Live Demo

Python • Scikit-learn • TF-IDF • NLP • Streamlit

Developed a three-class sentiment analysis system for social media text using NLP preprocessing and TF-IDF feature extraction.
Compared Logistic Regression and Multinomial Naive Bayes, selecting Logistic Regression based on validation performance.
Deployed the trained model with Streamlit for real-time sentiment prediction.

E-commerce Sales & Profitability Analysis

GitHub

Python • Pandas • NumPy • Matplotlib • Seaborn

Performed data cleaning, feature engineering, and exploratory analysis on transaction-level e-commerce data.
Analyzed sales trends, product performance, customer behavior, regional performance, and profitability.
Created analytical visualizations using Pandas, NumPy, Matplotlib, and Seaborn to identify business patterns.

AgroFarm AI

GitHub Live Demo

Python • Gemini • ChromaDB • RAG • Streamlit

Developed an agriculture advisory application combining Generative AI, RAG, and Agentic AI for grounded, field-aware farming guidance.
Integrated Gemini, ChromaDB, TF-IDF, Open-Meteo, and Streamlit into the application.

Languages

English • Urdu • Punjabi