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When I initially started working on this book for the class, it was focused on tiny machine learning. However, as I began writing, it became clear that machine learning systems, whether big or small, share the same fundamentals. Consequently, I've been gradually trying to move away from explicitly discussing or mentioning tiny ML in the book. Nevertheless, I haven't fully addressed this yet, and it needs to be cleaned up through all the chapters. The goal is to focus on ML systems broadly as a category and using Cloud, Edge and Tiny as just examples of classes of ML deployments.
The text was updated successfully, but these errors were encountered:
When I initially started working on this book for the class, it was focused on tiny machine learning. However, as I began writing, it became clear that machine learning systems, whether big or small, share the same fundamentals. Consequently, I've been gradually trying to move away from explicitly discussing or mentioning tiny ML in the book. Nevertheless, I haven't fully addressed this yet, and it needs to be cleaned up through all the chapters. The goal is to focus on ML systems broadly as a category and using Cloud, Edge and Tiny as just examples of classes of ML deployments.
The text was updated successfully, but these errors were encountered: