Tutorial

1. Introduction (includes the MBP Algorithm)
2. Creating the training and the test datasets
3. Defining the topology of the neural networks
4. Configuring the activation functions of the neurons
5. Defining the neural network learning configuration
6. Training a neural network - Part I (regression)
7. Training a neural network - Part II (classification)
8. Copying data and graphics
9. Initialize, view, save and load the neural network weights
10. Load and save a neural network
11. Generate C code from a trained neural network
12. Analyzing the input sensitivity of a neural network