Book Image

AI Crash Course

By : Hadelin de Ponteves
5 (2)
Book Image

AI Crash Course

5 (2)
By: Hadelin de Ponteves

Overview of this book

Welcome to the Robot World … and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination.
Table of Contents (17 chapters)
16
Index

What are CNNs used for?

CNNs are mostly used with images or videos, and sometimes with text to tackle Natural Language Processing (NLP) problems. They are often used in object recognition, for example, predicting whether there is a cat or a dog in a picture or video. They are also often used with deep Q-learning (which we will discuss later on), when the environment returns 2D states of itself, for example, when we are trying to build a self-driving car that reads outputs from cameras around it.

Remember the example in Chapter 9, Going Pro with Artificial Brains - Deep Q-Learning, where we were predicting houses' prices. As inputs, we had all of the values that define a house (area, age, number of bedrooms, and so on), and as output, we had the price of a house. In the case of CNNs, things are very similar. For example, if we wanted to solve the same problem using CNNs, we would have images of houses as inputs and the price of a house as output.

This diagram...