Download Tiny Machine Learning QuickStart PDF Free - Full Version
Download Tiny Machine Learning QuickStart by Simone Salerno in PDF format completely FREE. No registration required, no payment needed. Get instant access to this valuable resource on PDFdrive.to!
About Tiny Machine Learning QuickStart
Be a part of the Tiny Machine Learning (TinyML) revolution in the ever-growing world of IoT. This book examines the concepts, workflows, and tools needed to make your projects smarter, all within the Arduino platform. You’ll start by exploring Machine learning in the context of embedded, resource-constrained devices as opposed to your powerful, gigabyte-RAM computer. You’ll review the unique challenges it poses, but also the limitless possibilities it opens. Next, you’ll work through nine projects that encompass different data types (tabular, time series, audio and images) and tasks (classification and regression). Throughout the book, you’ll apply three different approaches to TinyML: traditional algorithms (Decision Tree, Logistic Regression, SVM), Edge Impulse (a no-code online tools), and TensorFlow for Microcontrollers. Each has its strengths and weaknesses, and you will learn how to choose the most appropriate for your use case. TinyML Quickstart will provide a solid reference for all your future projects with minimal cost and effort. For electronics hobbyists and developers with a basic understanding of Tensorflow, ML in Python, and Arduino-based programming looking to apply that knowledge with microcontrollers. Previous experience with C++ is helpful but not required.
Detailed Information
| Author: | Simone Salerno |
|---|---|
| Pages: | 340 |
| Language: | English |
| File Size: | 12 |
| Format: | |
| Price: | FREE |
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