Overview
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Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning.
Syllabus
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Introduction
- Welcome
- What you should know
- Using the exercise files
- Neurons and artificial neurons
- Gradient descent
- The XOR challenge and solution
- Neural networks
- Activation functions
- Backpropagation and hyperparameters
- Neural network visualization
- Understanding the components in Keras
- Setting up a Microsoft account on Azure
- Introduction to MNIST
- Preprocessing the training data
- Preprocessing the test data
- Building the Keras model
- Compiling the neural network model
- Training the neural network model
- Accuracy and evaluation of the neural network model
- Convolutions
- Zero padding and pooling
- Preprocessing and loading of data
- Creating and compiling the model
- Training and evaluating the model
- Enhancements to CNNs
- Image augmentation in Keras
- ImageNet challenge
- Working with VGG16
- Next steps
