321. Convolutional Neural Networks in One Dimension

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This course kicks off a machine vision sequence, starting out with all the fundamentals of convolutional neural networks in one dimension for maximum clarity. We will extend Cottonwood to handle convolutional architectures and apply it to classifying electrically-measured heartbeats as healthy or irregular.

Course Curriculum

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Your Instructor

Brandon Rohrer
Brandon Rohrer

I love solving puzzles and building things. Machine learning lets me do both. I got started by studying robotics and human rehabilitation at MIT (MS '99, PhD '02), moved on to machine vision and machine learning at Sandia National Laboratories, then to predictive modeling of agriculture DuPont Pioneer, and cloud data science at Microsoft. At Facebook I worked to get internet and electrical power to those in the world who don't have it, using deep learning and satellite imagery and to do a better job identifying topics reliably in unstructured text. Now at iRobot I work to help robots get better and better at doing their jobs. In my spare time I like to rock climb, write robot learning algorithms, and go on walks with my wife and our dog, Reign of Terror.