Demystifying Artificial intelligence: Simplified AI and Machine Learning concepts for Everyone (English Edition)
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About this ebook
So, the basic knowledge of AI/ML becomes mandatory for everyone. This book is your first step to start the journey in this field. Along with basic concepts of fields, like machine learning, deep learning and NLP, we will also explore how big companies are using these technologies to deliver greater user experience and earning millions of dollars in profit.
Also, we will see how the owners of small- or medium-sized businesses can leverage and integrate these technologies with their products and services. Leveraging AI and ML can become that competitive moat which can differentiate the product from others.
In this book, you will learn the root concepts of AI/ML and how these inanimate machines can actually become smarter than the humans at a few tasks, and how companies are using AI and how you can leverage AI to earn profits.
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Book preview
Demystifying Artificial intelligence - Prashant Kikani
CHAPTER 1
Introduction
In this introductory chapter, we will explore some of the basic terms related to artificial intelligence (AI) such as machine learning, deep learning, data science, neural networks, etc.
After reading this, you will know what the field
really is, what each term means, and how each part connects to the other. We will take a look at all this by keeping it short and simple.
Structure
In this chapter, we will cover the following topics:
What is data?
How to convert images, text, and audio data into numbers?
What is AI?
Subfields of AI
Types of AI
What is ML?
What is DL?
What are artificial neural networks and how are they built?
What is "deep" in deep learning?
Advantages/limitations of DL
What is data science?
Why do we need AI?
Why does automation matter?
Machine learning and maths
Why is ML so dependent on maths?
Objectives
After studying this chapter, you should be able to:
Learn about various terms related to AI and their correlation
Have a general idea about what an AI system might look like
Understand how machines can do something better than humans and what makes them so much better at some tasks
What is data?
Before we start discussing AI and machine learning, let’s first discuss data.
Data is the main reason why AI and ML algorithms/models are able to learn anything meaningful. It plays a crucial role in the performance of any ML model. In general, data can mean anything like tables in spreadsheets, images, videos, audios, text, track records, etc. We use data to teach machines/computers, but, guess what, machines can only understand numbers. Other than numbers, it can’t understand anything. Data is the crux of every ML model, and data is the only thing that the ML model gets from us. Quality and quantity of data are very important as that’s what the model uses to learn something. As long as we can somehow convert something into numbers, it becomes
data for the machine learning models.
(By the way, a model is just an algorithm that learns to capture patterns in data. Basically, we teach models to make predictions in the future.)
It is okay for spreadsheet tables as they already have numbers, but what about images, audios, videos, or text? They are not numbers. Then, how can a machine learn from them?
Computers only understand numbers; nothing more or less. They operate in 0 and 1. So, we need to communicate with computers in numbers because that’s what they understand.
Well, if the data is not in numbers, we convert it into numbers.
How? Let’s see.
1. Text
Text is made from different words. We give each word a unique number. Let’s say, there are a total of 80,000 unique English words in our test dataset. We give each of them a unique number. So, the sentence "machine learning is very easy becomes something like
19768 45734 3 2349 459". Now, machines/computers can read this sentence. This process is called encoding in technical terms. Did you get the idea? We replaced each word with its corresponding number to convert text into numbers. While doing this, we maintain the order of the words.
2. Images
Actually, an image is already in the number format. When we capture a photo or shoot a video from a mobile phone or camera, it’s stored in numbers in memory. So, unlike text data, there is no need to exclusively convert images into numbers.
An image is nothing but a group of pixels in a certain order.
A pixel is the smallest unit of an image. Every pixel has a number associated with it. So, in a nutshell, an image is nothing but thousands of numbers in a certain order. For example, let’s take a look at the following image:
Figure 1.1: How a pixel looks like if we zoom in a photo
If we zoom the image to some extent, we can see each pixel. You may have seen these types of pixels in your mobile or camera. Each number in a pixel represents how much of these fundamental colors (i.e. Red, Green, and Blue) contribute to a particular