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RBOT 240

Machine Learning

Data driven learning is key to modern autonomous systems. This course will focus on the theory and algorithms in Machine Learning. Regression, Neural networks, Deep learning, Classification, Random forests, Support vector machines, PCA, clustering, EM and more.
At the end of the course, students will be able to:
Design and implement machine learning solutions using SOA methods
Implement and test solutions using libraries such as Caffe, scikit-learn or OpenCV
Apply Deep learning using Caffe/Theano
Use Jupyter notebooks using rich visualization techniques to drive and journal design models

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