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The target audience for this book is primarily **embedded systems engineers** who want to understand and implement machine learning algorithms on resource-constrained devices. However, the book also caters to other professionals with an interest in the field of tiny machine learning (**TinyML**).
# Topics covered
## Topics Covered
The book covers a wide range of topics related to embedded machine learning, providing a comprehensive understanding of the field. The topics covered include:
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By encompassing these aspects, our aim is to make this book a go-to resource for anyone interested in developing intelligent applications on embedded systems.
## **Course Requirements**
## Prerequisites
* **Basic Programming Knowledge**: It is *recommended* that readers have some prior experience with programming, preferably in Python. Understanding variables, data types, control structures, and basic programming concepts will facilitate comprehension and engagement with the book.