About

Welcome to my website/portfolio. I have a bachelors in math and am a graduate from a Python Development Bootcamp in Seattle. Comparing that experience to my other bootcamp - the Marine Corps scenic Parris Island - I would have to say the Python involved significantly less screaming. Recently I have been learning about creating dockerizied AWS solutions for generative AI interfaces.


I'm a technology professional with over a decade of experience in data analysis, passionate about solving real-world problems with innovative solutions. My skills include project management, team leadership, and business development, and I'm always eager to stay on top of emerging technologies. In my free time, I enjoy tabletop gaming and exploring the Pacific Northwest with my totally awesome dog.

Basic Information
Email:
b s w a r d (A T) g m a i l (D O T) c o m
LinkedIn:
Visit My LinkedIn Page
GitHub:
Visit My GitHub Page
Code Wars:
Visit My CodeWars Page
Photo:
Brian's photo
Portfolio
Selected Python Projects
  • Fake News Detector
    • Tech Used: Python, Jupyter/Kaggle, Machine Learning, Web Scraping, Pandas, Numpy, BeautifulSoup, JSON, Request, Spacy, Trafilatura
    • Purpose: This code uses numpy, pandas, and scikit-learn (sklearn) to read and preprocess a dataset of news articles to train on. The code prompts the user to input a URL and then extracts the text content from the page using BS and Traf. Finally, it outputs the predicted label (fake or real) for the extracted text using the previously trained model. The tools, libraries, and skills on display in this code include data preprocessing, machine learning, web scraping, HTTP requests, and text extraction.
  • Web Text Extractor
    • Tech Used: Python, Jupyter/Kaggle, Web Scraping, BeautifulSoup, Trafilatura, JSON, textwrap
    • Purpose: This code defines functions to extract text from a single web page using a combination of libraries like BeautifulSoup, Trafilatura, and Requests. It takes a user input URL, extracts the text from the given URL, and wraps the text into paragraphs of 80 characters per line using the textwrap library. If there are any anomalies in the extraction process, it returns NaN.
  • Code Wars Practice
    • Tech Used: Vanilla Python
    • Purpose: Code Wars is designed to test your programming chops. This GitHub contains all my demonstrative skill-based work amassed since graduating Code Fellows. Problems are approached without using methods to simulate whiteboard questions and responses.
  • Flask User Post API
    • Tech Used: Python, JSON, Jinja, Pytest, API Creation, Data Formatting
    • Purpose: This is a simple Flask application that defines an API endpoint for receiving user posts. The /user-post endpoint accepts a JSON payload containing a username and text field, restructures the data, and returns it as a JSON response.
  • Website Portfolio
    • Tech Used: Python, JSON, HTML, Bootstrap, CSS
    • Purpose: This is a simple portfolio built using Flask to provide a simple interface with clean delivery of information, or static files like photos or resumes. Most of the site is auto populated via a JSON file. This allows for content updates to be made without touching the HTML itself allowing non-tech savvy end users' more control over their site's content without the need of a web guru.
  • Mortgage Data Analysis
    • Tech Used: Python, Machine Learning, Jupyter/Kaggle, Django, Numpy, Pandas, MatPlotLib, Tailwind, Next.js
    • Purpose: Performed Logistical Regression on publicly available data to determine given categorical data if a user will be approved for a loan.
  • Data Structures and Algorithms
    • Tech Used: Python, Stack, Queue, Node, Hashtable, Graphs, Binary Tree, Binary Search Trees, Linked List
    • Purpose: Demonstrative knowledge of fundamental data structures and common approaches such as, but not limited to: insertion sorts, merge sort, and weighted graph traversal.
  • Chess Board Checker
    • Tech Used: Python, Jupyter/Kaggle, Numpy, Pandas, MatPlotLib
    • Purpose: To determine if two randomly placed chess queens can "see" each other, and then return a boolean response to the user along with a graphical representation for visual confirmation.
  • Housing Hunter Hero
    • Tech Used: Python, BeautifulSoup, Web Scraping, JSON, HTML, Data Pipelining
    • Purpose: To get a quick simple list of available properties with details and URL to the listing. This was done by taking in a user supplied zipcode, scraping a well known real estate site for data, and returning that information formatted for use by the user.
  • Data Extraction Automation
    • Tech Used: Python, RegEx, Data Formatting, Pytest
    • Purpose: Demonstrative logic to iterate through simulated web scraped data and use regular expressions to extract the needed data.
Education
Certificate In Advanced Python Development

Code Fellows - Seattle, Washington

  • Over 1,000 hours of combined lecture, projects, and lab time in Python.
  • Over 600 hours of combined lecture, projects, and lab time in JavaScript.
Bachelors of Arts in Mathematics

Wesleyan University - Middletown, Connecticut

Selected Courses:

  • Abstract Linear Algebra
  • Graph Theory
  • Complex Analysis
  • Abstract Algebra
  • Topology

Professional Skills
Programming Languages: Python, R, SQL, JavaScript, HTML, CSS, C++

Tools: PyCharm, VS Code, Jupyter, Django REST API, Pandas, Flask, SciKitLearn, Docker, BeautifulSoup,Excel, Google Sheets, Tableau, WSL, Ubuntu, NumPy, Django, MongoDB, Matplotlib, Bootstrap, Seaborn, Chart.JS, Budget Analysis, API Engineering, Data Mining, Data Cleaning, Data Visualization, Database Management, Cross-Functional Collaboration, Technical Instruction, Agile and Waterfall Methodologies, Exploratory, Quantitative, and Qualitative Data Analysis

Database Management: MySQL, postgreSQL, MongoDB, SQLite3, Pivot Tables, VLookUp

Project Management: CSM, Lean Six Sigma, and Google Project Management Certifications