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Embedded Machine Learning with Microcontrollers de Cem Ünsalan

Embedded Machine Learning with Microcontrollers

Autor Cem Ünsalan, Berkan Höke, Eren Atmaca
en Limba Engleză Hardback – 25 oct 2024
This textbook introduces basic embedded machine learning methods by exploring practical applications on STM32 development boards. Students will be guided in implementing machine learning methods to be deployed and tested on microcontrollers throughout the book, with the theory behind the implemented methods also emphasized.
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Specificații

ISBN-13: 9783031709111
ISBN-10: 303170911X
Pagini: 420
Dimensiuni: 160 x 241 x 29 mm
Greutate: 0.74 kg
Editura: Springer

Notă biografică

Dr. Cem Ünsalan is currently a full professor and head of the Department of Electrical and Electronics Engineering at Marmara University, Turkey. Prior to that he was a member of the faculty in the Department of Electrical and Electronics Engineering at Yeditepe University, Turkey, where he established the DSP Lab and taught microprocessor and digital signal processing courses for 15 years. Dr. Ünsalan received his BSc degree from Hacettepe University; his MSc degree from Bogazici University; and his PhD from The Ohio State University. His research focuses on digital signal processing on embedded systems, computer vision, and remote sensing. He has published extensively on these topics in respected journals.
H. Deniz Gürhan received his BSc (2010) from Yeditepe University, Turkey. He is pursuing a Ph.D. degree in digital signal processing and embedded systems at the same university and works as a research assistant in the DSP Lab. His research focuses on digital signal processing, digital control, and embedded systems.
M. Erkin Yücel received his BSc and MSc from Yeditepe University, where he is pursuing a PhD in embedded systems and works as a research assistant in the DSP Lab. His research focuses on digital and analog signal processing, IoT, sensors, and embedded systems.

Cuprins

Introduction.- Hardware to Be Used in the Book.- Software to Be Used in the Book.- Data Acquisition From Sensors.- Introduction to Machine Learning.- Classification.- Regression.- Clustering.- The Tensorflow Platform and Keras API.- Fundamentals of Neural Networks.- Embedding the Neural Network Model to the Microcontroller.- Multi-layer Neural Networks.- Convolutional Neural Networks.- Recurrent Neural Networks.- Training the Multi-layer Neural Network on the Microcontroller.- Convolution Neural Networks.- Recurrence in Neural Networks.

Textul de pe ultima copertă

This textbook introduces basic and advanced embedded machine learning methods by exploring practical applications on Arduino boards. By covering traditional and neural network-based machine learning methods implemented on microcontrollers, the text is designed for use in courses on microcontrollers and embedded machine learning systems. Following the learning-by-doing approach, the book will enable students to grasp embedded machine learning concepts through real-world examples, providing them with the design and implementation skills needed for a competitive job market. By utilizing a programming environment that enables students to reach and modify microcontroller properties easily, the material allows for fast implementation of the developed system. Students are guided in implementing machine learning methods to be deployed and tested on microcontrollers throughout the book, with the theory behind the implemented methods also emphasized. Sample codes and real-world projects are available for readers and instructors. The book will also be an ideal reference for practicing engineers and electronics hobbyists. 
  • Teaches embedded machine learning system design skills needed for today’s job market;
  • Thoroughly explains each concept and provides illustrated examples and projects;
  • Includes sample codes, course slides, and a solutions manual.