This month’s recommended reading selections all deal with the hot topic of artificial intelligence (AI), machine learning (ML), and data strategies. As companies begin to feel the pressure to have strategies in place to maximize data collection usage, these books contain helpful lessons for all knowledge levels.
Publishers, especially, need to understand how to use collected data to implement ML protocols that will increase engagement, purchases, and referrals.
The following book picks offer a wide range of valuable information, lessons, solutions, and tools to help you enter the world of AI. Read on…
Book Picks: Understanding the power of data, artificial intelligence, and machine learning
Data Driven: Harnessing Data and AI to Reinvent Customer Engagement by Tom Chavez, Chris O’Hara, and Vivek Vaidya
“Using the latest technologies—cloud, mobile, social, Internet of Things (IoT), and artificial intelligence (AI)—we have more data about consumers and their needs, wants, and affinities than ever before.”
Building an effective data strategy is essential given the changes in the way consumers find information and search for and buy products and services. Consumer use of digital technology, social media, and e-commerce and the large amounts of data gathered from them require businesses to make major adjustments in their marketing efforts.
This book explains how to create targeted marketing plans that encourage brand loyalty and inspire purchases, deliver personalized interactions, provide better customer service, gather and organize data, and use AI and IoT to predict the future direction of markets.
Learn the principles for building a data strategy and the sources of “data-driven power,” and get a glimpse into several top companies that have used these data-driven strategies to increase customer engagement.
Data Science for Executives: Leveraging Machine Intelligence to Drive Business ROI by Nir Kaldero
“Leaders don’t have to be scientists to unlock the power of AI technology that is already radically altering the industrial landscape. If you’re ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.”
Data Science for Executives provides a clear picture of the impact that machine intelligence has on business and offers strategies for using its powers for profitability.
This book shares informative case studies, guiding principles, and steps to incorporate machine intelligence into your organization. Learn how to use all the data that flows into your organization to enhance your business.
Pragmatic AI: An Introduction to Cloud-Based Machine Learning by Noah Gift
“Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science.”
Get familiar with “off-the-shelf cloud offerings” from Amazon, Google, and Microsoft, and see verified techniques using the Python data science ecosystem. The workflows and examples given will help to streamline each step and build scalable solutions. In understanding how machine learning solutions work, you’ll know what you can achieve with them and how to extend their purpose.
Step by step, walk through building cloud-based AI/ML applications and learn how they solve real-world issues in sports marketing, project management, product pricing, real estate, and more. Get expert guidance and the added benefit of case studies that give you the information you need to solve data science problems in any environment.
Machine Learning For Beginners: Guide to Understand Machine Learning by Matthew Kinsey
“Through machine learning, intelligent systems can be built. The core dependents include data, algorithms, automation, iteration, scalability, and modeling. Being an application of artificial intelligence, a branch of computer science, machine learning is a trending subject that is aimed at revolutionizing the world.”
Machine learning uses algorithms that are able to learn from gathered data and initiate responses. The algorithms analyze data and calculate the frequency of the parts of the data utilized. The findings from the calculations result in an automatic interaction with users.
Machine Learning for Beginners provides details about, as well as problems with, machine learning and where it can be applied. This book also covers the topic of neural networks (a computer system modeled on the human brain and nervous system) and how they can be used in the areas of artificial intelligence and deep learning.
Applied Artificial Intelligence: A Handbook For Business Leaders by Mariya Yao and Adelyn Zhou
“If you want to drive innovation by combining data, technology, design, and people to solve real problems at an enterprise scale, this is your playbook.”
Applied Artificial Intelligence is a practical guide for business leaders looking to reap the benefits of adopting machine learning technology to enhance the productivity of their organizations and their communities’ quality of life.
Learn how to lead successful AI projects, create a team of experts, and test and design solutions. This book will also help you make concrete business decisions through applications of artificial intelligence and machine learning.
Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations by Ilya Katsov
“A comprehensive and indispensable reference for anyone undertaking the transformational journey towards algorithmic marketing.” — Ali Bouhouch, CTO, Sephora Americas
This guide to advanced marketing automation shares various techniques—verified by key technology, advertising, and retail companies—with marketing strategists, data scientists, product managers, and software engineers. Marketing topics covered include programmatic micro-decisioning, targeted promotions and advertisements, e-commerce search, recommendations, pricing, and assortment optimization.
Deep Learning Fundamentals: An Introduction for Beginners by Chao Pan
“Our book may be the best one for beginners. It’s a step-by-step guide for any person who wants to start learning artificial intelligence and data science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses.”
This beginners’ step-by-step guide introduces the reader to the fundamental principles of artificial intelligence, machine learning, and deep learning with examples, and includes models in the form of graphs and images.
Targeting a variety of readers, this book is for the novice interested in algorithms and their part in making predictions; the software developer and engineer looking to branch out into the machine learning field; and the professional in the AI and ML field who may want a look at current techniques and approaches. Readers will have an elementary understanding of deep learning concepts and algorithms and get a technical background in both deep learning and neural networks.
Note: Quotes are from Amazon book descriptions.
If you’d like to share something you’ve read, drop us a note. Also check out the Technology for Publishing blog, and keep up with the latest industry news coverage by signing up for our This Week in Publishing emails and monthly Publishing Innovations newsletter.
Posted by: Monica Murphy
