Abhishek Kuppili

I’m a Data Science undergraduate with a strong foundation in Python, SQL, and Machine Learning. I’m passionate about transforming raw data into meaningful insights that help teams make better decisions.

In my internship, I worked on data analysis and visualization using Python libraries such as Pandas and Matplotlib. I also developed predictive models with Scikit-learn, applying data preprocessing, feature selection, and model evaluation, while collaborating on Python-based solutions for business use cases.

My projects include a Customer Churn Prediction model for a Telecom dataset, where I achieved 80% accuracy. I used Logistic Regression, Random Forest, and Decision Trees, and used correlation and feature importance to identify key churn drivers, then visualized patterns with Seaborn and Matplotlib.

I’m building my technical depth through certifications like Data Analytics Essentials and IoT, and through hands-on work across EDA, data cleaning, feature engineering, and predictive modeling. I enjoy taking structured steps—from analysis to modeling to visualization—to deliver clear, actionable results.