A Stock tracking app using object-oriented programming in Python. It processes historical stock data and generates visual reports with libraries like matplotlib and pandas.
Created a decision tree model in R to classify iris flower types with 97.78% accuracy. Covered model training, visualization, and performance evaluation.
A deep learning project using TensorFlow and Keras to build a CNN (Convolutional Neural Network) model Using Jupyter Notebook that classifies images from the CIFAR-10 dataset with ~71% accuracy.
A Python based tool that process aircraft maintenance logs (CSV files) to detect patterns, summarize issues, and generate insightful visual reports. Designed for aviation teams to simplify data analysis and improve maintenance tracking.
