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Artificial Intelligence II – Hands-On Neural Networks (Java)

Hopfield networks, neural networks, gradient descent and backpropagation algorithms explained step by step
(471 reviews)
4,991 students
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Platform: Udemy
Video: 4h 54m
Language: English
Next start: On Demand

Table of contents


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
•how to construct an autoassociative memory with neural networks
Section 3:
•what is back-propagation
•feedforward neural networks
•optimizing the cost function
•error calculation
•backpropagation and gradient descent
Section 4:
•the single perceptron model
•solving linear classification problems
•logical operators (AND and XOR operation)
Section 5:
•applications of neural networks
•classification (Iris-dataset)
•optical character recognition (OCR)
•smile-detector application from scratch
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!

You will learn

✓ Basics of neural networks
✓ Hopfield networks
✓ Concrete implementation of neural networks
✓ Backpropagation
✓ Optical character recognition


• Basic Java

This course is for

• This course is recommended for students who are interested in artificial intelligence focusing on neural networks
Software Engineer
My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model.
Take a look at my website if you are interested in these topics!
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Platform: Udemy
Video: 4h 54m
Language: English
Next start: On Demand

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