Core Technologies: Python, MySQL, Spark, Tableau, Pandas, NumPy, Matplotlib, Seaborn, SciKitLearn, Anaconda, Jupyter Notebooks, Git/GitHub
Core Competencies: Data Storytelling, Applied Statistics, Machine Learning, Natural Language Processing, Classification, Regression, Clustering, Time Series Analysis, Anomaly Detection
Primary Focus: Machine Learning
I am deeply passionate about and skilled at technologies like machine learning and neural networking. My enthusiasm drives me to stay updated with the latest advancements in the field, enabling me to leverage the power of these technologies to derive meaningful insights from data. This, combined with my expertise in data analytics and strong written and verbal skills (Juris Doctor) allow me to extract valuable insights from complex datasets and effectively communicate findings to both technical and non-technical stakeholders.
My Capstone Project: Blue Chip Predict
This project predicts the next quarter’s revenue for a U.S. Blue Chip company. We define blue chip company as a large company that is well-established, financially sound, and has an excellent reputation. This project takes a dataset consisting of 80 quarters worth (20 years) of 38 different national economic, social, political, and environmental measures. It uses that data to train a machine-learning model and a neural network to use this quarter’s data to predict next quarter’s revenue for three blue-chip companies: Ford, Starbucks, and AT&T, however, the models have been designed to predict the revenue for any company that past quarterly revenues can be found.
