Data Science
DS 4440: Practical Neural Networks
Lecture - 4 credits
ND
EI
IC
FQ
SI
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WD
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CE
- Offers a hands-on introduction to modern neural network ("deep learning") tools and methods.
- Covers the fundamentals of neural networks and introduces standard and new architectures from simple feed forward networks to recurrent neural networks.
- Also covers stochastic gradient descent and backpropagation, along with related fitting techniques.
- Emphasizes using these technologies in practice, via modern toolkits.
- Specifically introduces Keras (together with TensorFlow) and PyTorch, which are illustrative of static and dynamic network implementations, respectively.
- Reviews applications of these models to various types of data, including images and text.
Offers a hands-on introduction to modern neural network ("deep learning") tools and methods. Show more.
Pre-requisites