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Machine Learning for Embedded Systems with ARM Ethos-U NPU

ARM NPU Hardware

Vp Product, google ventures

ML Hardware Accelerator

ML MCU

Low Power Machine Learning Accelerators
Learn AI, ML, and TensorFlow Lite for microcontrollers with ARM NPU

What's included?

  • 11 Chapters
  • 1 Certification
  • 80 Slides
  • 110 Video

What Will You Learn?

Technical Details on Machine Learning Models Inference on Embedded Devices:
  • TFLM Explained
  • ML Models from Training stage to run on embedded devices
  • ARM NPU Ethos Families: Machine Learning Hardware Accelerator
  • ARM Machine LEarning Compiler: Vela Compiler
  • Understanding ML FaltBuffer representation
  • Running Key Word Spotting and Image recognization examples on Alif-E7 NPU based Boards

Personal Bonus

As a Bonus in This Course, You Will Receive: 
  • Familiarization with Machine Learning Inference Concept
  • Step by Step to cross compile Alif E7 examples on windows machine and run it on embedded device 
  • Live execution of key word spotting and image recognization on Alif E7 Board
  • Support on any course releated questions and informations
Meet the instructor

Sebastian Helmut

Sebastian Helmut is an Embedded Systems Architect with over 15 years of experience in embedded systems software development. He has worked with major semiconductor companies, such as STMicroelectronics, NXP Semiconductors, and Qualcomm, gaining extensive experience with both ARM and RISC-V architectures, embedded systems devices, embedded software development, and a variety of related topics.

Whether you're a student eager to start a career in embedded systems or an engineer looking to expand your technical toolkit, Sebastian’s courses are designed to accelerate your learning and equip you with the skills needed to succeed in today’s tech-driven world.

Patrick Jones - Course author
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