Artificial Intelligence II – Neural Networks in Java

Description :

This course is about artificial neural networks. Artificial intelligence and machine learning are getting more and more popular nowadays. In the beginning, other techniques such as Support Vector Machines outperformed neural networks, but in the 21th century neural networks again gain popularity. In spite of the slow training procedure, neural networks can be very powerful. Applications ranges from regression problems to optical character recognition and face detection.

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!