Artificial Intelligence for Dummies (9781119467588) by Mueller John Paul; Massaron Luca

Author:Mueller, John Paul; Massaron, Luca [Mueller, John Paul]
Language: eng
Format: epub
ISBN: 9781119467588
Publisher: Wiley
Published: 2018-04-10T00:00:00+00:00

Chapter 11

Improving AI with Deep Learning

IN THIS CHAPTER

Beginning with the limited perceptron

Getting the building blocks of neural network and backpropagation

Perceiving and detecting objects in images using convolutions

Using sequences and catching them with RNNs

Discovering the creative side of AI thanks to GANs

Newspapers, business magazines, social networks, and nontechnical websites are all saying the same thing: AI is cool stuff and it’s going to revolutionize the world because of deep learning. AI is a far larger field than machine learning, and deep learning is just a small part of machine learning.

It’s important to distinguish hype used to lure investors and show what this technology can actually do, which is the overall purpose of this chapter. The article at https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/ contains a useful comparison of the roles of the three methods of manipulating data (AI, machine learning, and deep learning), which this chapter describes in detail.

This chapter helps you understand deep learning from a practical and technical point of view, and understand what it can achieve in the near term by exploring its possibilities and limitations. The chapter begins with the history and basics of neural networks. It then presents the state-of-the-art results from convolutional neural networks, recurrent neural networks (both for supervised learning), and generative adversarial networks (a kind of unsupervised learning).

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