ST-HardwareDes/MachLrngSyst
Study architectural techniques for efficient hardware design for machine learning (ML) systems including training and inference. Course has three parts. First part deals with ML algorithms: regression, support vector machines, decision tree, and naive Bayes approaches. Second part deals with convolutional and deep neural network models.