DATA 542 - Neural Networks & Deep Learning

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This course teaches the foundations of Neural Networks and DeepLearning. Students entering into this course should have, at minimum, a background indata preprocessing, cleaning, manipulation, and dimensionality reduction within python.Through an applied learning project, you will learn how to implement a machine learningproject from design to implementation in the context of neural networks. Topics we willcover include the basic building blocks of neural networks, RNNs, convolutional networksand computer vision, backpropagation basics and strategies (including inductive transfer ap-proaches), differences between technical implementations (i.e., TensorFlow, Keras, Torch), and more.