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Practical Artificial Intelligence: An Enterprise Playbook
Artificial Intelligence (AI) can bring about radical improvements in the workplace and industry at large; the technology is sound, the math behind it robust. The market is enthusiastic and billions of dollars a year are being invested in AI; billions more will be spent over the coming years. Nevertheless, AI projects often never get off the ground, fail early, or disappoint in the long run. In this book we explain how to implement AI correctly and dramatically improve your chances of success. The truth of the matter is that the reasons for past failures, though multiple, are easy to spot and avoid. The remedy does not require advanced mathematical skills or deep insights into the world of coding and application development. In this book, we show you how to approach your AI project from start to finish correctly. We provide you with a practical playbook to use in your day to day work, one that takes you from an initial strategy, through to a successful deployment to deliver transformative results. We provide you with an unbiased and truly independent perspective on AI: exploring its strengths and its weaknesses, where it should and should not be used, and even going so far as to prime you on the 'dark side' of AI. There is no doubt that AI provides great power to change the way you work, but as Uncle Ben of Spiderman fame advised us, "With great power comes great responsibility." AI can go wrong, and when it does, it can have devastating consequences. The guidance we provide in this book will help you to avoid those problems and lead you to success.
- GenresArtificial Intelligence
142 pages, Kindle Edition
Published September 1, 2019
25 people are currently reading
30 people want to read
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Displaying 1 - 5 of 5 reviews
September 14, 2020
Practical Artificial Intelligence breaks down big concepts to demystify AI and puts them into simple, digestible terms. It allows the reader to look at AI applications, explaining not only what AI can do for your business but how to go about pursuing an implementation in depth. With a step-by-step roadmap, it explains key things you need to know like sourcing the right talent to data and use case selection. Finally, it examines the “dark side” of AI that often goes overlooked, including what could happen if you don’t account for biases and blind spots. All in all, concepts are explained clearly yet succinctly. Anyone seeking a quick but valuable guide to AI will find it here!
July 14, 2021
The book is a breezy read. While it doesn't really offer anything new or insightful, it is a good read for a non-tech reader who wants to get a little holistic introduction to the practical issues pertaining to adoption of AI inside the enterprise.
December 13, 2020
Good practical guide for implementing artificial intelligence.
September 20, 2019
Right from the way its cover was designed – nice touch, The Creation of a Bot, I guess – to the deft way a very interesting but not-easy-to-handle subject was presented, this book appealed to me. Whilst my background is not strictly IT, I am involved, to some extent, with the rapid changes occurring at work, brought about due to automation and machine learning. It is this involvement in automation projects that prompted me to pick up this book. Reading the book helped me gain a better understanding of the intricacies involved, what an AI/ML team potentially looks for, the importance of data collection and the likely pit-falls an organization will invariably come across when it undertakes such ambitious but necessary projects.
Every chapter is presented in a very simple, lucid way and technical jargon is resorted to only where it is unavoidable. My favorite is Chapter 4, for the user-friendly way the authors set about explaining the differences between various ML methods. And, key points are presented at the end of every chapter, making the book read like a reference book.
Whether you are directly involved in automation projects or are just one of the end-users, I suggest you read the book. You can thank me later.
A quick word of praise: not about the content of the book but about how it is presented. It is every writer’s dream to achieve a perfect balance between the quantity of words and the quality of content. Too verbose, you lose the reader’s interest. Too brief, you run the risk of sounding incomplete. Kashyap and Alan, in this book, seem to have achieved just the right balance. Good work!
Every chapter is presented in a very simple, lucid way and technical jargon is resorted to only where it is unavoidable. My favorite is Chapter 4, for the user-friendly way the authors set about explaining the differences between various ML methods. And, key points are presented at the end of every chapter, making the book read like a reference book.
Whether you are directly involved in automation projects or are just one of the end-users, I suggest you read the book. You can thank me later.
A quick word of praise: not about the content of the book but about how it is presented. It is every writer’s dream to achieve a perfect balance between the quantity of words and the quality of content. Too verbose, you lose the reader’s interest. Too brief, you run the risk of sounding incomplete. Kashyap and Alan, in this book, seem to have achieved just the right balance. Good work!
October 21, 2019
Good one
Who want to start something in ai.
Ai recruiters.
Al business startup companies.
For basic knowledge.
Know failures before fail
Who want to start something in ai.
Ai recruiters.
Al business startup companies.
For basic knowledge.
Know failures before fail
Displaying 1 - 5 of 5 reviews