Johns Hopkins University 3 credits Physics & Astronomy
Neural networks have changed the ways we interact with data and think about statistics. For scientists, it is important to understand the fundamental concepts behind these systems, why they work, what their potential and limitations are. This course will open the black box of neural networks and address some of the theoretical foundations of Machine Learning. It will include aspects of statistics in high dimensions, information theory, optimization, architectures, as well as concepts from neuroscience. We will alternate between theory and applications in python. More at https://bit.ly/3LEAg7D
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