Artificial Intelligence II – Neural Networks in Java

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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!