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1. What is a neural network?
2. How to train the network with simple example data (1:10)
3. ANN vs Logistic regression (06:42)
4. How to evaluate the network (07:14)
5. How to use the network for prediction (09:23)
6. How to estimate the weights (10:25)
7. Understanding the hidden layers (16:30)
8. ANN vs regression (20:56)
9. How to set up and train an ANN in R (23:08)