Deep Learning - Part I
This badge confirms completion of the seven week course Deep Learning - Part I with instructor Jeremy Howard at the Data Institute at the University of San Francisco.
The learning outcomes of this certificate include:
- The basic algorithms and architecture underlying Deep Learning
- Understanding Convolutions and Stochastic Gradient Descent (SGD)
- Implementation and mastery of the components of a Convolution Neural Network (CNN)
- Applying Deep Learning to problems in computer vision, including VGG
- Understanding the structure of a Recurrent Neural Network (RNN) and using current technologies including creating layers by hand in keras; sequence and stateful RNNs; simple RNN in Theano
- Exposure to best practices and tools for RNN and CNN including pseudo-labeling and combining validation/training sets, resnet multi input and multi output nets, localization and gated recurrent units