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AI Crash Course

AI Crash Course

By : Hadelin de Ponteves
4 (24)
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AI Crash Course

AI Crash Course

4 (24)
By: Hadelin de Ponteves

Overview of this book

Welcome to the Robot World … and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination.
Table of Contents (17 chapters)
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16
Index

Beginning the AI journey

Being a young AI scientist, I remember my first days in AI very well. This is important because this book is a crash course in AI. You don't need any prior knowledge of the field to work through the chapters.

In this book, I will explain the solid foundations of AI, while making sure to answer all the questions that I had back when I started in this field in detail. This means that everything will be explained step by step, and your learning process will follow a smooth path, supported by the relevant logic.

Having the right information at your fingertips is not enough to successfully break into the AI world. What you also need is energy, enthusiasm, and excitement. Even better, you need passion, and ideally obsession, about the subject. As an experienced tutor of online courses, I hope to pass on my knowledge and, most importantly, my passion.

In this book, you will go on a journey together with me, taking a path through a world of exciting AI applications, including many real-world case studies in the chapters. The applications will follow an increasing level of difficulty, from the simplest model in AI, to a much more advanced level.

For each of the AI applications, I will focus mostly on the intuition needed to understand them, and then, for those interested in the mathematics and pure theory behind the application, I will provide those as an option. The reason why I choose to focus on intuition rather than math is not only because I want to make this book easy to understand for everyone, but also because, in order to perform well in AI today, it is extremely important to have the right intuition. When you're solving a problem with AI, you have to figure out which model best fits your problem environment, and you can only do that when you have the proper intuition of how each AI model works.

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AI Crash Course
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