Abdul Khadar Shaik

Rice Leaf Disease Detection – PRCP-1001
Capstone Internship Project

Developed a comprehensive machine learning solution to detect and classify rice leaf diseases using image data. Conducted exploratory data analysis (EDA), applied data augmentation techniques, and built classification models to identify three major diseases: leaf smut, brown spot, and bacterial leaf blight. Compared multiple models and documented performance metrics to recommend the best model for deployment. Addressed challenges related to limited data and class imbalance through preprocessing and augmentation strategies.

FIFA 20 Player Analysis – PRCP-1004
Capstone Internship Project

Performed in-depth data analysis on FIFA 20 player statistics to uncover insights into player performance, country-wise representation, and offensive player compensation. Applied clustering techniques to group players based on skill attributes and visualized trends such as age vs. overall rating. Delivered a comprehensive report answering key analytical questions and explored historical comparisons between top players like Messi and Ronaldo. Utilized Python, pandas, matplotlib, and scikit-learn for data exploration and modeling.

House Price Prediction – PRCP-1020
Capstone Internship Project

Developed a predictive model to estimate house prices using advanced regression techniques such as Random Forest and Gradient Boosting. Conducted thorough exploratory data analysis (EDA) on housing data with 79 features, identifying key factors influencing price variations. Engineered meaningful features and built a robust machine learning pipeline to deliver accurate predictions. Provided actionable insights and recommendations for home buyers based on area, price, and preferences.

• Introduction to Python, Data Types, Basic Data structures (Tuple, List, Sets, Dictionary).