From the course: Machine Learning in Mobile Applications
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Introduction to ML Kit
From the course: Machine Learning in Mobile Applications
Introduction to ML Kit
ML Kit is Google's answer to Core ML. It was announced in 2021 at Google I/O and takes a slightly different philosophy on how machine learning for mobile devices should work. Unlike Apple, Google has a much deeper relationship with machine learning professionals with their TensorFlow product. That is a product aimed squarely at data scientists, and likely isn't what many developers will know. It is a complex tool and requires deep understanding of machine learning, in particular deep learning. TensorFlow and scikit-learn are two of the most popular frameworks to use by data scientists. For the vast majority of developers, learning these frameworks to the extent you would need in order to create a really accurate model is not worth the effort. For mobile developers, these models also do not usually run natively on mobile devices, so even with knowledge of TensorFlow, it is not useful for mobile application development. In order to make TensorFlow available to other devices, Google made…
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Introduction to ML Kit3m 53s
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Selecting a model2m 57s
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Adding the SDK to a mobile app10m 33s
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Calling the model10m 43s
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Running the app3m 2s
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Challenge: Implement the image labeling model2m
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Solution: Implement the image labeling model3m 4s
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