TensorFlow Lite - The Professional Course

TensorFlow Lite - The Professional Course

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Because of the large size of the most successful machine learning (ML) models, mobile and embedding applications based on artificial intelligence (AI) have relied on models stored on large remote servers. That brings many disadvantages to those applications: the need for an internet connection, the latency caused by the communication to the server, battery draining due to the network connection, and the sharing of the user's data.

During this course, you will learn how to overcome those limitations by compressing and optimizing state-of-the-art ML models to run 100% at the edge. The goal of this course is to teach you the fundamentals of model compression and optimization, along with the entire pipeline of model embedding and profiling used by industry professionals.

For who is this course?

- Machine learning engineers.

- Mobile software engineers.

- Enthusiasts of AI and mobile applications in general.

What will you learn?

- Week 1: How to embed machine learning models on mobile devices (FREE)

- Week 2: How to evaluate the performance of machine learning models on mobile apps.

- Week 3: How to optimize machine learning models for mobile devices.

- Week 4: How to develop an optimized machine learning-based mobile app from scratch.

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TensorFlow Lite - The Professional Course
1 Hotmarter Year

TensorFlow Lite - The Professional Course was created by the software engineers Michel Meneses and Luiz Reis.

Michel Meneses (https://www.linkedin.com/in/michel-meneses/) is a software engineer specializing in machine learning. He has obtained his bachelor's degree in computer engineering and his master's degree in computer engineering from the Federal University of Sergipe (UFS), Brazil.

Luiz Reis (https://www.linkedin.com/in/luizvitorreis/) is a software engineer focused on embedded systems. He has obtained his bachelor's degree in mechatronics engineering from the University of Brasilia (UnB), Brazil.

Both authors have been developing their professional careers in the field of artificial intelligence applied to mobile devices, where they perform R&D on artificial intelligence at the edge and develop mobile products used by millions of people around the world.

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