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<script type="text/javascript" src="https://platform.linkedin.com/badges/js/profile.js" async defer></script>This is Josh | |
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Josh's LinkedIn Profile |
Overview: A machine learning computer vision model to utilize retail video cameras to learn more about the shopping habits of customers.
The Model:
- The Jupyter Notebook outlining each section of code in my customer counter python file.
The Code:
- The python code for a still image object detector.
- The python code to count human objects crossing a line of demarcation. Intended to count customers crossing a specific plane intended to replicate the entrance/exit of a retail store.
Convolutional Neural Networks - 12.13.2018
- A brief introduction to how CNNs work and why they're the preferred neural network for image recognition.
How to Write a Function in Python - 12.19.2018
- A helpful guide on best practices to follow when writing your own Python functions.
Generate a random dataset - 12.20.2018
- Working Python code (converted from Jupyter Notebook to HTML) to create a basic (pseudo)random dataset (.ipynb file is on main Github repository.) This is a decent starting point to build more robust datasets for testing statistical models.
Getting to Know Pandas - 01.08.2019
- Using Daniel Chen's "Pandas for Everyone" to work through data analysis exercises. I plan to use this as a code snippet repository, reference for the future, and demonstration of my proficiency with the Pandas library.
Openstack Cloud Project - Spring 2019
- Setting up a proof-of-concept Openstack cloud for Regis University - College of Computer and Information Sciences (CC&IS) department using three used servers. The goal is to secure funding for additional new hardware and eventually have a private cloud with large compute resources for student and department research projects.