000			03120nam a2200229 4500
005			20251029180158.0
008			251029b |||||||| |||| 00| 0 eng d
020			_a9783031694202
082			_a006.31 _bUNS
100			_aÜnsalan, Cem _925940
245			_aEmbedded machine learning with microcontrollers: _bapplications on arduino boards
260			_aCham _bSpringer _c2025
300			_axiii, 371 p.
365			_aEURO _b64.99
500			_aTable of contents: Front Matter Pages i-xiii Download chapter PDF Introduction Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 1-6 Hardware to Be Used in the Book Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 7-15 Software to Be Used in the Book Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 17-23 Data Acquisition from Sensors Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 25-49 Introduction to Machine Learning Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 51-81 Classification Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 83-127 Regression Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 129-163 Clustering Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 165-182 The TensorFlow Platform and Keras API Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 183-197 Fundamentals of Neural Networks Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 199-231 Multilayer Neural Networks Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 233-253 Embedding the Neural Network Model to the Microcontroller Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 255-284 Convolutional Neural Networks Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 285-321 Recurrence in Neural Networks Cem Ünsalan, Berkan Höke, Eren Atmaca Pages 323-357 [https://link.springer.com/book/10.1007/978-3-031-69421-9]
520			_aThis 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 (https://link.springer.com/book/10.1007/978-3-031-69421-9)
650			_aData science
650			_aNetwork---analysis _915209
700			_aHöke, Berkan _925941
700			_aAtmaca, Eren _925942
942			_cBK _2ddc
999			_c10479 _d10479