Zach Wilsterman

Machine Learning Engineer

Hi, I'm Zach! I am a results-driven machine learning engineer with a proven background in project coordination and management. Highly skilled in communication and teaching, I have an eye for detail and exceptional time management ability. I am proficient in data research and analytics, and in implementing machine learning models using current technologies such as Tensorflow and PyTorch.

Click here to view my resume!

Technologies

  • Languages:
    • C
    • Python
  • Data Processing:
    • NumPy
    • Pandas
    • SciPy
    • Apache Hadoop
  • Databases:
    • MySQL
    • SQLite
    • MongoDB
    • Firestore
  • Data Visualization:
    • Plotly
    • Dash
    • Matplotlib
    • Seaborn
  • Machine Learning:
    • Tensorflow
    • Keras
    • PyTorch
    • OpenCV
    • Scikit-Learn
  • Cloud:
    • Amazon Web Services
    • AWS SageMaker
    • Google Cloud Suite

Projects

TASM Visitor Check-in Portal

github.com/conkobar/tasm-visitor-portal

  • A digital check-in system built for the Tulsa Air and Space Museum
  • Collects, securely stores, and efficiently processes digital visitor data to facilitate museum grant and funding applications
  • Responsible for creation of self-contained dashboard to read, process, and display database insights in an intuitive format
Technologies Used: Python, Pandas, Dash, Docker, Google Cloud Run, Firestore

YOLO Object Detection

github.com/wilstermanz/object_detection

  • Custom implementation of the YOLO algorithm to classify objects in images
  • Employs CV2 to outline objects and add confidence and class name
Technologies Used: Python, Tensorflow, NumPy, CV2

Space Bubbles

github.com/wilstermanz/space-bubbles

  • Arcade-style game inspired by Space Invaders and Bubble Shooter
  • Created during the Holberton Hack Sprint in a three person team
  • Responsible for collision detection, game logic, and artwork
Technologies Used: Python, Pygame, REST API, SQLite

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