This project entailed designing and analyzing advanced algorithms and data structures using C++. The project emphasized core concepts like algorithmic complexity and performance analysis while applying Object-Oriented Programming principles such as Templates, Inheritance, and Polymorphism. I developed and implemented algorithms, optimized performance, and expanded my skills in pointers and dynamic memory allocation to tackle complex problems efficiently.

This project involved creating multiple machine learning projects using Python in Jupyter Notebooks. I developed models including KNN, Decision Trees, Logistic Regression, Linear Regression, Random Forest, Gradient Boosting, Neural Networks (NNs), Convolutional Neural Networks (CNNs), and Natural Language Processing (NLP). Projects included predicting customer churn, forecasting Airbnb listing prices, classifying handwritten digits with a CNN, and analyzing book reviews for sentiment in both supervised and unsupervised learning contexts.

This research project focused on extracting and validating lake temperature data in the Adirondack Region using Landsat 5 and 7. Utilizing Python, I processed Landsat Level 2 Atmospherically Corrected surface reflectance data, applied cloud filters through Google Earth Engine, and integrated over 10,000 in-situ temperature data points from 135+ lakes. The project involved satellite temperature validation and trend analysis to assess the accuracy and reliability of satellite-derived temperature observations.