Machine Learning Engineer, Software Developer
I am a Software Developer focusing on Machine Learning.
My work involves putting data to work by extracting the hidden meaning in data. Machine learning, data processing and data analysis are the tools. Making model-based recommendations or decisions is what I do.
I love to turn research papers in to proof-of-concept demos and kick the tires of new software or technologies. I’m looking for more projects like the ones below so free to reach out!
Kaggle PLAsTiCC: A survey of approaches for classification of an aperiodic timeseries dataset from Kaggle.
Tri-Training: Use unlabeled data for supervised learning! The paper is from an Amazon researcher in Cambridge MA and was used for wake-word detection but the approach can be applied anywhere.
Whole-image Classification using Kiras/Tensorflow: This is a self-driving car that (in realtime) classifies images from a front-mounted camera. It is an end-to-end Tensorflow CNN deployed to Raspberry Pi.
The Bootstrap: A principled technique to establish statistical significance to test results. Combined with T-tests this is important to have in the tool belt.