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The Essential Beginner’s Guide to AI

A Breakdown of Artificial Intelligence and Machine Learning to Elevate Your Career and Simplify Everyday Life

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The Essential Beginner’s Guide to AI

By: Samuel Thorpe
Narrated by: Tom Brooks
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About this listen

Master Artificial Intelligence in no time, even if you're a total beginner or a tech novice with our essential guide — Empower your career and simplify your daily life! Does the world of AI and machine learning seem intimidating, complex, or out of reach? Are you interested in diving into the realm of AI but have no idea where to start? Are you overwhelmed by endless information and complex terminologies that seem to make AI learning more challenging? You're not alone!

Statistical studies show that a significant percentage of individuals interested in AI feel overwhelmed at the beginning. However, it's crucial to understand that mastering artificial intelligence doesn’t have to be as hard as you might believe. Even if you're starting from scratch and have just begin your journey in the tech world, it is possible to grasp and apply AI concepts without wasting endless hours or getting lost in complexity.

Introducing The Essential Beginners Guide to, a comprehensive guide that breaks down AI and machine learning in a way that is easy to understand for anyone, regardless of their tech proficiency. You might worry if this book is difficult to understand for someone without a tech background. We get that. This guide isn't like other textbooks that overload you with technical jargon and complex concepts. It's designed to be easily digestible and practical, written in clear, plain English that anyone can comprehend — and that's what makes it an "Essential Beginner's Guide".

Whether you're looking to boost your career, implement AI in your projects, or simply want to understand how AI is transforming the world, our book is your one-stop solution. If you're determined to decode the world of AI and adopt a future-facing mindset, don't wait another minute.

©2024 Daniel Troast (P)2024 Daniel Troast
Machine Theory & Artificial Intelligence

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