Book Image

AI Blueprints

By : Dr. Joshua Eckroth, Eric Schoen
Book Image

AI Blueprints

By: Dr. Joshua Eckroth, Eric Schoen

Overview of this book

AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code.
Table of Contents (14 chapters)
AI Blueprints
Foreword
Contributors
Preface
Other Books You May Enjoy
Index

Summary


In this chapter, we've demonstrated how to design and implement a CNN to detect and recognize logos in photos. These photos were obtained from social media using the Twitter API and some search keywords. As photos are found, and logos were detected, records of the detections were saved to a CSV file for later processing or viewing.

Along the way, we looked at the origin of the term deep learning and discussed the various components that led to a revolution in ML in the last few years. We showed how a convergence of technologies and sociological factors helped this revolution. We've also seen multiple demonstrations of how far we have come in such a short amount of time – with very little code, a set of training examples (made available to researchers for free), and a GPU, we can create our deep neural network with ease.

In the next chapter, we'll show how to use statistics and other techniques to discover trends and recognize anomalies such as a dramatic increase or decrease in the...