Artificial Intelligence II - Neural Networks in Java |
Section 1:
- what are neural networks
- modeling the human brain
- the big picture
Section 2:
- Hopfield neural networks
Section 3:
- what is back-propagation
- feedforward neural networks
- optimizing the cost function
- error calculation
- backpropagation and resilient propagation
Section 4:
- the single perceptron model
- solving linear classification problems
- logical operators (AND and XOR operation)
Section 5:
- applications of neural networks
- clustering
- classification (Iris-dataset)
- optical character recognition (OCR)
In the first part of the course you will learn about the theoretical background of neural networks, later you will learn how to implement them.
If you are keen on learning methods, let's get started!
Who this course is for:
- This course is recommended for students who are interested in artificial intelligence focusing on neural networks
- Get the course