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Neural networks

Dive into the world of neural networks, the building blocks of modern artificial intelligence. Learn how these computational models mimic the structure and function of the human brain to process data, recognise patterns, and make predictions.

Topics

1. What is a neural network?

Neural networks have become a cornerstone of modern artificial intelligence (AI), powering innovations across various domains, from voice assistants like

2. Feedforward neural networks: everything you need to know

Feedforward neural networks (FNNs), often referred to as multi-layer perceptrons (MLP), are one of the simplest forms of neural networks.

3. What are Convolutional Neural Networks (CNNs)?

What are Convolutional Neural Networks (CNNs)? Convolutional Neural Networks (CNNs) are specialized types of neural networks that can automatically and adaptively learn

4. Introduction to Recurrent Neural Networks (RNNs)

Recurrent Neural Networks (RNNs) are a class of artificial neural networks specifically designed to handle sequential data, making them highly effective

5. Neural networks: Introduction to generative adversarial networks

Generative Adversarial Networks (GANs) represent a revolutionary approach to generative modeling. They are a powerful class of artificial neural networks

6. Neural networks: How to optimize with gradient descent

An important element that has led to the success of neural networks is optimization. Optimization in neural networks directly influences how

7. Transformer models: What are they, and how do they work?

Transformers have redefined how machines understand and generate human language, and their influence is now extending into other domains like

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