Generative Deep Learning with Python

Chapter 1 Conclusion

In this introductory chapter, we've taken our first steps into the vast and exciting world of Deep Learning. We started with the basics of artificial neural networks, understanding the building block of these networks—the artificial neuron—and how the activation functions play a significant role in these networks.

We then delved into an overview of Deep Learning, where we saw what makes it different from traditional Machine Learning and why it's gained such popularity in recent years. We also explored various types of Deep Learning models, such as Feedforward Neural Networks (FNNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Autoencoders (AEs), and Generative Adversarial Networks (GANs).

However, ...