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What is TinyML?

TinyML has been gaining traction due to the development of hardware and software ecosystems that support it. The tool has made it possible to implement machine learning models in low-energy systems, like microcontrollers, TinyML can be used in a wide range of sectors, including agriculture, industrial predictive maintenance, and customer experience. It can also be used for computer vision, visual wake words, keyword spotters, gesture recognition, and more.

Datacamp

26 Aug 2024

What is Tiny Machine Learning (TinyML)?
TinyML is a type of machine learning that allows models to run on smaller, less powerful devices. It involves hardware, algorithms, and software that can analyze sensor data on these devices with very low power consumption, making it ideal for always-on use-cases and battery-operated devices.

All around us every day
Machine learning models play a prominent role in our daily lives – whether we know it or not. Throughout the course of a typical day, the odds are that you will interact with some machine learning model since they have permeated almost all the digital products we interact with; for example, social media services, virtual personal assistance, search engines, and spam filtering by your email hosting service. 

Despite the many instances of machine learning in daily life, there are still several areas the technology has failed to reach. The cause? Many machine learning models, especially state-of-the-art (SOTA) architectures, require significant resources. This demand for high-performance computing power has confined several machine learning applications to the cloud – on-demand computer system resource provider.  


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Originally posted February 2023

https://www.datacamp.com/blog/what-is-tinyml-tiny-machine-learning

For more:

Machine Learning, Neural Network, Infrastructure

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