A seasoned Data Scientist and Software Engineer with over 10 years of experience in Information Technology, Software Engineering, Data Science, and Data Engineering. My expertise lies in developing high-quality solutions for diverse industries, including e-commerce, aerospace, supply chain, and financial technology.
Is it possible to track a person and their movement with a moving camera? I explored this with a Raspberry Pi and moving camera, and possibly exploring the idea of tracking a toddler (my son).
Using a Raspberry Pi and the Pimoroni Pan-Tilt HAT, I was able to utilize OpenCV and its many capabilities to track Objects (including face-detection). I was able to leverage the use of a Haar Cascade algorithm as well as YOLOv4-tiny (with the Darknet Distibuted-Neural-Network) to accomplish this, as well as create a User-Interface for easy interaction.
Inspired by the HBO Series, Silicon Valley, this is a re-creation of Jian-Yang's infamous Hotdog/Not-Hotdog App. This app uses a convolutional neural net (CNN) that can run a prediction on whether a picture contains an image of a hotdog or not.
I pulled textual-data from two similar subreddits using my webscraping skills, and compared the two data-sets using Supervised Machine Learning. I utilized a Bayesian model, among other models, to decipher where the entry came from, and analyzed the results to deduce which model performed best.
The two subreddits used are the "AMA" subreddit and the "AskReddit" subreddit. It is worth noting that I removed some data to make it more challenging for the Machine Learning Algorithm to make a decision.
Through exploratory analysis of CDC and EPA data we wanted to evaluate a model that could be helpful for analyzing air pollutants with the thought of creating information for people with respiratory illness.
Knowing that increasing Air Quality Index (AQI) can negatively impact people with respiratory illensses, we wanted to evaluate the realtionship with air pollutants, temperature, day of the week, and month to see if we could identify any relationship to overall daily air quality data (from the EPA website).
Looking at electrical usage data from previous years, I used Forecasting to make a Predictive-Model that predicts Electrical consumption in North Carolina. I selected North Carolina because North Carolina appears to be the most average State out of the whole United States, based on this 2016 article from Business Insider. This was mostly completed within 6 hours (with a few caveats clearly outlined in the repository ReadMe file).
I enjoy spending quality time with my wife and son, and cooking up some delicious food.
I have a deep passion for learning especially about technology, and figuring out how things work.
In my free time, I enjoy reading and listening to audiobooks, especially on topics related to innovation and creativity.
Music has been a significant part of my life; I also used to play bass in a band in Denver, Colorado before moving to North Carolina and I also play guitar.
Currently I am learning to play drums and piano in my spare time.
