BrokĀ Bucholtz
Software Engineer at Vitgo LLC
Mosinee, Wisconsin, United States
Summary
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Top SchoolBrok Bucholtz is a software engineer with 11 years of experience specializing in applied machine learning and bridging the gap between models and end users. He has shipped ML and deep learning projects for organizations like Udacity and Azumio, contributing TensorFlow labs and image-classification work used in self-driving and educational repositories. As a co-founder and current engineer at small ventures, he balances product-minded engineering with hands-on model development and data normalization best practices. Based in Mosinee, Wisconsin, he pairs a UW-Milwaukee CS degree with a Udacity ML Nanodegree, and his open-source contributions reveal a practical focus on reproducible training pipelines and applied quantitative models for trading and vision tasks.
11 years of coding experience
7 years of employment as a software developer
High School Diploma, High School Diploma at Marshfield High SchoolBachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at UW-MilwaukeeMachine Learning Engineer Nanodegree, Machine Learning Engineer Nanodegree at Udacity
English
Stackoverflow
56reputation
6kreached
3answers
0questions
Github Skills (22)
python10
image-classification10
pandas10
machine-learning10
numpy10
deep-learning10
tensorflow10
neural-network10
data-analysis10
image-processing9
data-normalization9
finance9
statistical-models9
modeling9
jupyter-notebook9
Programming languages (3)
Github contributions (5)
udacity/CarND-TensorFlow-Lab
Oct 2016 - Apr 2017
TensorFlow Lab for Self-Driving Car ND
Role in this project:
ML Engineer
ML EngineerContributions:91 commits, 12 PRs, 62 pushes in 6 months
Contributions summary:Brok's commits primarily focused on developing a TensorFlow neural network for a self-driving car project. Their contributions involved creating a basic TensorFlow model, implementing data normalization techniques for image features, and fixing test cases. The user also added code for one-hot encoding of labels and implementing a TensorFlow example for the project. These efforts demonstrate a focus on building and refining a machine learning model within the context of a self-driving car application.
vehicle-detectiondeep-learningself-drivingmachine-learningtensorflow
udacity/artificial-intelligence-for-trading
Sep 2018 - Mar 2019
Content for Udacity's AI in Trading NanoDegree.
Role in this project:Data Scientist
Data ScientistContributions:16 commits, 7 pushes in 5 months
Contributions summary:Brok contributed to the implementation of Module 4, which appears to be related to a multi-factor model within the context of AI for trading. The provided code differences show the addition of a substantial Jupyter Notebook (`project_4_starter.ipynb`), indicating that the user likely worked on the model's design, implementation, and possibly initial analysis. The inclusion of imports from libraries like `cvxpy`, `numpy`, and `pandas` suggests they focused on the mathematical and analytical aspects of the model.
nanodegreeudacitymachine-learningtradingartificial-intelligence
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