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HarvardX: Applications of TinyML

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Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.

Applications of TinyML
6 semanas
2–4 horas por semana
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Sobre este curso

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Do you know what happens when you say “OK Google” to a Google device? Is your Google Home always listening?

Following on the Foundations of Tiny ML course, Applications of TinyML will give you the opportunity to see tiny machine learning applications in practice. This course features real-world case studies, guided by industry leaders, that examine deployment challenges on tiny or deeply embedded devices.

Dive into the code for using sensor data for tasks such as gesture detection and voice recognition. Focusing on the neural network of the applications, specifically on training and inference, you will review the code behind “OK Google,” “Alexa,” and smartphone features on Android and Apple . Learn about real-word industry applications of TinyML as well as Keyword Spotting, Visual Wake Words, Anomaly Detection, Dataset Engineering, and Responsible Artificial Intelligence.

Tiny Machine Learning (TinyML) is one of the fastest-growing areas of deep learning and is rapidly becoming more accessible. The second course in the TinyML Professional Certificate program, Applications of TinyML shows you the code behind some of the world’s most widely-used TinyML devices.

De un vistazo

  • Institution HarvardX
  • Subject Análisis de datos
  • Level Intermediate
  • Prerequisites
    • Fundamentals of TinyML course or sufficient relevant experience:
      • Basic Scripting in Python
      • Basic usage of Colab
      • Basics of Machine Learning
      • Basics of Embedded Systems
  • Language English
  • Video Transcripts اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated programs
  • Associated skillsArtificial Neural Networks, Android (Operating System), Machine Learning, Anomaly Detection, Smartphone Operation, Deep Learning, Speech Recognition

Lo que aprenderás

Omitir Lo que aprenderás
  • The code behind some of the most widely used applications of TinyML
  • Real-word industry applications of TinyML
  • Principles of Keyword Spotting
  • Principles of Visual Wake Words
  • Concept of Anomaly Detection
  • Principles of Dataset Engineering
  • Responsible AI Development

Plan de estudios

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  • Chapter 1.1: Welcome to Applications of TinyML
  • Chapter 1.2: AI Lifecycle and ML Workflow
  • Chapter 1.3: Machine Learning on Mobile and Edge IoT Devices - Part 1
  • Chapter 1.4: Machine Learning on Mobile and Edge IoT Devices - Part 2
  • Chapter 1.5: Keyword Spotting
  • Chapter 1.6: Data Engineering for TinyML Applications
  • Chapter 1.7: Visual Wake Words
  • Chapter 1.8: Anomaly Detection
  • Chapter 1.9: Responsible AI Development
  • Chapter 1.10: Summary

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

Este curso es parte del programa Applied Tiny Machine Learning (TinyML) for Scale Professional Certificate

Más información 
Instrucción por expertos
3 cursos de capacitación
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5 meses
2 - 4 horas semanales

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