808-381-0751 | mnguyenngo@gmail.com | Github | LinkedIn
Software developer with experience in machine learning and data science in the process of making a career transition from structural engineering. I enjoy working on personal projects and collaborating with others as much as possible. In addition to keeping up with the latest machine learning tools, I was driven to understand how to build REST APIs and web applications in order to easily deploy and demonstrate my work to the online community.
Measureyes | August 2018
First place winner in Globant's "Future of Retail" Hackathon.
- Product mockup for a solution that would bring A/B testing strategies to the physical retail space, specifically storefronts and window displays.
- Using computer vision and a simple camera setup, we can track the amount of head-turns vs. the amount of foot traffic to calculate the head-turn rate (HTR), which can be thought of as the direct analog of the click-through rate.
presume.xyz (WIP) | August 2018
- Shell application that manages the content for a resume and returns the applicable and optimized response for common job application questions.
builtby.xyz | July 2018
- Leverage open data provide by Seattle.gov to build a platform that will display permit applications on a map of Seattle.
- Use information extraction and NLP to automatically retrieve information from PDFs regarding the developer, architect, and other trades involved in the permit.
In Your Own Words | June 2018
- Application that quizzes the user on machine learning concepts scraped from The Machine Learning Wikibook. Scoring is done by calculating cosine similarity and word-matching.
- Deployed the application using Flask (formally at iyow.xyz).
archi.codes | May 2018
- Used sPaCy's natural language model to analyze the text in the building code regulations. Extracted keywords to create a graph-style database with nodes and edges.
- Deployed the application using Flask and AWS. The user can enter a search query or a chunk of text to be analyzed. Keywords are highlighted and hyperlinked to specific webpage with relationships to Wikipedia where relevant.
study-script | March 2018
- Command line utility to take the Markdown content from a Jupyter notebook and serve multiple choice, fill-in-the-blank questions to the user.
- The goal of the project was to improve memory retention of the course content and to share the tool with fellow classmates.
- Python
- Numpy
- Matplotlib
- Scikit-Learn (Machine Learning)
- Pytorch & TensorFlow (Deep Learning)
- Flask
- Javascript
- SQL / MongoDB
- REST API
- Git
- HTML/CSS
- Certificate, Data Science Immersive
- MS, Civil Engineering | 3.85 GPA
- MS, Civil Engineering | 3.26 GPA
- Structural engineer and project manager for various single-family homes and multi-family apartment buildings.
- Authored assessment reports for the renovation and rehabilitation of existing aquarium exhibits.
- Built 3D structural models for the new construction of a large assembly structure and place of worship.
- Authored a technical guide for reinforcing older single-wall houses to improve hurricane resistance as part of a commission.
- Project engineer for various types of projects including new condominium buildings, concrete parking structures, a new elementary school campus.
- Most notable project was the flagship Walgreens store in Waikiki.