Titlebook: Embedded Machine Learning with Microcontrollers; Applications on STM3 Cem ünsalan,Berkan H?ke,Eren Atmaca Textbook 2025 The Editor(s) (if a

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Intelligent Human — Machine SystemssorFlow provides a platform to perform all these operations. The Keras API will simplify life for use while benefiting from TensorFlow. Therefore, we will consider both in this chapter. To do so, we will start with their installation. Then, we will explore constant and variable declarations in Tenso

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Springer Series in Pharmaceutical Statisticsis not sufficient enough to solve complex machine learning problems. Therefore, we should form a more powerful structure called multilayer neural networks, generally called neural networks. We will consider this structure in this chapter. To do so, we will start with the background information on ne

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Norio Matsumoto,Genshiro Kitagawato the microcontroller. To do so, we will benefit from TensorFlow Lite as the specialized version of TensorFlow for embedded systems (including microcontrollers). Hence, we will start with its properties. Then, we will show ways of converting TensorFlow and Keras models to TensorFlow Lite format. Mo

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Francesco Amigoni,Viola Schiaffonaticurrence. This will help us in forming neural network structures with memory capability. Hence, they will be more suitable for sequential data processing. To explain these concepts better, we will first associate recurrence with memory in this chapter. Afterward, we will introduce three popular neur

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978-3-031-70914-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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