Review of The AI Playbook

[Isaac Oh]

[Following is an official OnlineBookClub.org review of "The AI Playbook" by Eric Siegel.]

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5 out of 5 stars

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Are you a data scientist or just an individual with a monumental interest in machine learning and how it drives today's world? Then this informative book by Eric Seigel is just perfect for you.
 
The book is structured into six mainstream chapters that uncover, step by step, the intricacies of what Seigel calls bizML. They include value, target, performance, fuel, algorithm, and the final launch. Value, which is chapter one, discusses how to establish a business value proposition and how ML would affect operations to improve them. Target, which is the second step, involves defining what the ML model will predict for each case. Performance involves understanding model training and deployment and determining the project's performance level. Fuel is all about data preparation and training; algorithms involve generating predictive models for data; and deployment includes using models to render predictive scores and using those scores to improve business operations.
 
The first noteworthy thing about this book is Seigel's effortless ability to infuse his experiences and the experiences of others into the treasure trove of insights he delivers. Years of service have coalesced into profound knowledge and sound authority that is difficult to ignore. Throughout the book, the author is constantly saying, “This is what I've done, and this is what I've seen. Here is what works, and here's what doesn't work.” It takes another level of skill to write a book about a technical subject like machine learning and keep your readers glued to the end. Despite the length of the book and its subject matter, which is tailored to a unique audience, it is not boring, and that is applaudable. Another remarkable characteristic is how tall this book stands on the shoulders of impeccable research. Nothing makes a book richer and more solid than divulging necessary information backed up by research because it engineers belief and certainty. It also proves that the author was meticulous enough to do his or her homework, and there is nothing to dislike about this book.
 
The Al Playbook is a superb collection of insights, illustrations, examples, diagrams, and explanations broken down in the most simplified ways. It is said that if you cannot break down something in such a way that anyone can understand it, then you do not possess a comprehensive understanding of that subject matter. Eric Seigel doesn't just display comprehensive understanding; he proves that he has long evolved into an authentic authority in the field of machine learning, and this belief is reinforced at the start of every chapter, where there are small narrations of what each chapter contains. He also does a good job of dismantling common mainstream narratives and replacing them with the truth. This corrective procedure is my main motivation for giving this book 5 out of 5 stars, coupled with the fact that the book is professionally edited, as I found no errors that impeded the reading process. I love the use of elaborate descriptions and expositions that convey both the strengths and weaknesses of machine learning and the prerequisites for its success. In many ways, I consider this book a necessity not just for career scientists, researchers, or engineers but for the world at large.
 
Machine learning is changing how we interact with the world around us. Therefore, I recommend this book to those who want to know more about it. But I would mostly recommend this book for professional data scientists, engineers, technicians, and those who consistently encounter machine learning in their careers. I believe that this book will be useful in triggering a growth process for them by expanding whatever knowledge they already have.

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The AI Playbook
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[elitaa]

This book is really helpful to people who are passionate about mastering AI Hi-Tech.

[Donaking]

The review suggests that the book "The Al Playbook" by Eric Seigel is a highly informative and engaging read for individuals interested in machine learning. The author's ability to incorporate personal experiences and research-backed insights adds credibility and makes the book compelling. The reviewer praises the book's thorough explanations, illustrations, and examples that break down complex concepts. The book is described as professionally edited and error-free. Overall, the review strongly recommends the book for data scientists, engineers, and anyone wanting to gain a deeper understanding of machine learning.

[Rohith Kumar Pakala]

Thank you for your valuable insights, your review built interest in me to read this book. Great information is given by you about the book, thank you for that.