Machine Learning, Industrial IoT, Machine Vision, Robotics
I am a software developer focused on Industrial IoT, machine vision, robotics and machine learning. My toolset includes PyTorch, Torch Geometric, transfer learning, pretrained models, Colab, Django and Precise Automation robotics.
I like to keep on top of the latest ML techniques and “kick the tires” through proof-of-concept experiments. I’m always looking for projects like the ones below so free to reach out!
Graph Neural Network using PyG (Pytorch Geometric) In this project we model topic evolution on social media using a Twitter dataset of Covid-19 tweets. We use PyTorch Geometric, Sequence Encoder, HeteroConv and a BERT language model.
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 CNN deployed to Raspberry Pi.
Markov Logic Network is a new and exciting technique for modeling systems that have structure but are inherently probabilistic.
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.
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.
Industrial Internet-of-Things (IIOT)
Probabilistic Graphical Models
Speech Recognition and Synthesis