Book Image

Artificial Intelligence Business: How you can profit from AI

By : Przemek Chojecki
Book Image

Artificial Intelligence Business: How you can profit from AI

By: Przemek Chojecki

Overview of this book

We’re living in revolutionary times. Artificial intelligence is changing how the world operates and it determines how smooth certain processes are. For instance, when you go on a holiday, multiple services allow you to find the most convenient flights and the best hotels, you get personalized suggestions on what you might want to see, and you go to the airport via one of the ride-sharing apps. At each of these steps, AI algorithms are at work for your convenience. This book will guide you through everything, from what AI is to how it influences our economy and society. The book starts with an introduction to artificial intelligence and machine learning, and explains the importance of AI in the modern world. You’ll explore how start-ups make key decisions with AI and how AI plays a major role in boosting businesses. Next, you’ll find out how media companies use image generation techniques to create engaging content. As you progress, you’ll explore how text generation and AI chatbot models simplify our daily lives. Toward the end, you’ll understand the importance of AI in the education and healthcare sectors, and realize the risks associated with AI and how we can leverage AI effectively to help us in the future. By the end of this book, you’ll have learned how machine learning works and have a solid understanding of the recent business applications of AI.
Table of Contents (10 chapters)

From research to applications

Having discussed how research is done in AI, its now time to focus on applications. Assuming you already have a data science team in place and preliminary research on a problem you want to solve done, the next step is to gather and clean data. This process can be short if most of your business is digital with easy access to data, or long and painful if you have many sources to look at and data is far from clean (say, surveys of customers done in various formats). If thats the case, preprocessing is a task that would need a separate team to complete. Its especially essential for all the later work, so dont ignore cleaning data.

Applying research to business applications means using machine learning models on data coming from your business and measuring how well they behave compared to how you usually solve the problem at hand (e.g. time spent on a business process, marketing/sales, number of relevant leads). After receiving...