Section: 4. Neural Networks (EN) | Artificial Intelligence and Machine Learning Fundamentals

Section outline

Introduction

Welcome to the topic of Neural Networks! Neural networks are a key component of deep learning, a subset of machine learning that mimics the structure and function of the human brain. In this section, you will learn about the basic elements of neural networks, including neurons, layers, and activation functions. We will explore different types of neural network architectures, such as convolutional and recurrent neural networks, and their applications in solving complex problems. You will also gain hands-on experience in training and testing neural networks using popular tools and frameworks.
- Select activity 4.1 Neural networks
  
  4.1 Neural networks Page
  
  Students must
  
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- Select activity 4.2 Training of neural networks
  
  4.2 Training of neural networks Page
  
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- Select activity 4.3 Convolutional Neural Networks (CNN)
  
  4.3 Convolutional Neural Networks (CNN) Page
  
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- Select activity 4.4 Recurrent neural networks
  
  4.4 Recurrent neural networks Page
  
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- Select activity 4.5 K-Means algorithm
  
  4.5 K-Means algorithm Page
  
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- Select activity Exercise 10: Training neural networks
  
  Exercise 10: Training neural networks Assignment
  
  Students must
  
  Make a submission
- Select activity Exercise 11: VGG-16 Network and Image Classification Task
  
  Exercise 11: VGG-16 Network and Image Classification Task Assignment
  
  Students must
  
  Make a submission
- Select activity Exercise 12: K-Means algorithm
  
  Exercise 12: K-Means algorithm Assignment
  
  Students must
  
  Make a submission

Section outline

Introduction