Book Image

The Applied Artificial Intelligence Workshop

By : Anthony So, William So, Zsolt Nagy
Book Image

The Applied Artificial Intelligence Workshop

By: Anthony So, William So, Zsolt Nagy

Overview of this book

You already know that artificial intelligence (AI) and machine learning (ML) are present in many of the tools you use in your daily routine. But do you want to be able to create your own AI and ML models and develop your skills in these domains to kickstart your AI career? The Applied Artificial Intelligence Workshop gets you started with applying AI with the help of practical exercises and useful examples, all put together cleverly to help you gain the skills to transform your career. The book begins by teaching you how to predict outcomes using regression. You will then learn how to classify data using techniques such as k-nearest neighbor (KNN) and support vector machine (SVM) classifiers. As you progress, you’ll explore various decision trees by learning how to build a reliable decision tree model that can help your company find cars that clients are likely to buy. The final chapters will introduce you to deep learning and neural networks. Through various activities, such as predicting stock prices and recognizing handwritten digits, you’ll learn how to train and implement convolutional neural networks (CNNs) and recurrent neural networks (RNNs). By the end of this applied AI book, you’ll have learned how to predict outcomes and train neural networks and be able to use various techniques to develop AI and ML models.
Table of Contents (8 chapters)
Preface

Computer Vision and Image Classification

Deep learning has achieved amazing results in computer vision and natural language processing. Computer vision is a field that involves analyzing digital images. A digital image is a matrix composed of pixels. Each pixel has a value between 0 and 255 and this value represents the intensity of the pixel. An image can be black and white and have only one channel. But it can also have colors, and in that case, it will have three channels for the colors red, green, and blue. This digital version of an image that can be fed to a deep learning model.

There are multiple applications of computer vision, such as image classification (recognizing the main object in an image), object detection (localizing different objects in an image), and image segmentation (finding the edges of objects in an image). In this book, we will only look at image classification.

In the next section, we will look at a specific type of architecture: CNNs.

Convolutional...