There has been a lot of progress in the field of machine learning (ML) in the last five years. These days, a variety of ML applications are being used in our daily lives and we don't even realize it. Since ML has taken the spotlight, it would be helpful if we could use it to run deep models on mobile devices, which is one of the most used devices in our daily life.
Innovation in mobile hardware, coupled with new software frameworks for deploying ML models on mobile devices, is proving to be one of the major accelerators for developing ML based applications on mobile or other edge devices like tablet..
In this chapter, we will learn about Google's new library, TensorFlow Lite, which can be used to deploy ML models on mobile devices. We will train a deep learning model on the MNIST digits dataset and look at how we can convert...
