Week 8 Learning Material

Convolutional Neural Networks - Week 1

This week covered the following topics:

• Explain the convolution operation
• Apply two different types of pooling operations
• Identify the components used in a convolutional neural network (padding, stride, filter, ...) and their purpose
• Build a convolutional neural network
• Implement convolutional and pooling layers in numpy, including forward propagation
• Implement helper functions to use when implementing a TensorFlow model
• Create a mood classifer using the TF Keras Sequential API
• Build a ConvNet to identify sign language digits using the TF Keras Functional API
• Build and train a ConvNet in TensorFlow for a binary classification problem
• Build and train a ConvNet in TensorFlow for a multiclass classification problem
• Explain different use cases for the Sequential and Functional APIs

Applied Techniques

The labs in the Coursera modules are proving to be good introductions to applied techniques. This weeks labs had you use TensorFlow to train a model to recognize smiling faces (binary classification) and sign language digits (multiclass classification). It introduced the sequential and functional APIs and explained the benefits of functional. Have to admit I'm not fully grasping TF just yet but more to come in the following weeks.