This is a selection of data science work I’ve completed recently.
If you need someone to create or update a desktop or mobile app; or to help with a tricky data science / machine learning problem, I can help.
Before contacting me, I strongly suggest you read through my contract guidelines.
BYU-Idaho’s Machine Learning Course
In 2019, I redesigned BYU-Idaho’s machine learning course, and taught it for several semesters.
The course consists of a series of case-studies that teach guide students through the application of data analytics, data wrangling, and machine learning to real-world business problems.
Machine learning topics covered include model selection and evaluation, kNN, decision trees, ensemble models, gradient boosted trees, standard neural networks, convolutional neural networks, and recurrent neural networks.
Most importantly, the course teaches students how to translate a business problem to a machine learning problem, and how to translate a machine learning solution to actionable business insights.
A public index of the course materials may be found here.
Wipro ITI asked me to help them develop an interpretive glyph recognition system for customer data.
I worked with their engineering team to develop a multi-phase, semi-supervised machine learning algorithm to process raw spatial data.
The primary phase uses a set of heuristic processes to filter out noise and combine primitive shapes into interpretable glyphs. This is followed by a secondary phase that uses a series of post-processing pipelines to reinterpret glyphs according to their surrounding contexts.