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Débute 4 June 2026 05:23

Se termine 4 June 2026

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

Plongez dans le monde de l'intelligence artificielle avec notre cours "Intelligence Artificielle II - Pratique des réseaux de neurones (Java)" sur Udemy. Ce cours complet couvre tout, des bases des réseaux de neurones et des réseaux de Hopfield à la mise en œuvre concrète des réseaux de neurones, y compris la rétropropagation et la reconnaissance o.
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Aperçu

Delve into the world of Artificial Intelligence with our "Artificial Intelligence II - Hands-On Neural Networks (Java)" course on Udemy. This comprehensive course covers everything from the basics of neural networks and Hopfield networks to the concrete implementation of neural networks, including backpropagation and optical character recognition.

Whether you're a beginner or looking to deepen your understanding, this course offers step-by-step explanations of gradient descent, backpropagation algorithms, and much more.

What you'll learn:

  • Foundational knowledge of neural networks
  • Insights into Hopfield networks
  • Practical implementation of neural networks
  • Understanding backpropagation
  • Techniques for optical character recognition

This course is tailored for those interested in the cutting edge of artificial neural networks. With AI and machine learning's rising popularity, neural networks have regained prominence for their power despite slow training procedures.

They are now used in a variety of applications, from regression problems to face detection.

Course Outline:

  • Section 1:

    Introduction to neural networks, modeling the human brain, the big picture.

  • Section 2:

    Exploring Hopfield neural networks and constructing autoassociative memory.

  • Section 3:

    Comprehensive guide on back-propagation, feedforward neural networks, cost function optimization, and error calculation.

  • Section 4:

    Detailed look into the single perceptron model, solving linear classification problems, logical operators (AND and XOR operation).

  • Section 5:

    Practical applications of neural networks in clustering, classification (Iris-dataset), optical character recognition (OCR), and building a smile-detector from scratch.

Embark on this journey to unlock the potential of artificial neural networks and apply them to real-world problems. If you're eager to dive into the methods of neural networks with hands-on Java applications, this course is the perfect starting point. Let's get started!

Categories:

Artificial Intelligence Courses, Machine Learning Courses, Neural Networks Courses


Enseigné par

Holczer Balazs


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