[Update Links] Machine Learning on Android Demystified | Pluralsight

Machine Learning on Android Demystified | Pluralsight
English | Size: 297.15 MB
Genre: eLearning

What does it take to implement machine learning in your app? In this talk, Tatyana Casino will suggest different ways to approach this. There will be comparisons between cloud-based services and local (on-device) machine learning, focusing mostly on the latter. On-device predictions are happening strictly on a mobile device, giving you the benefit of keeping the users’ data private and not depending on the network connection. Features like Google Lens Suggestions, Call Screening, and Live Caption are all leveraging on-device ML. However, the ML models should be prepared and optimized for efficiency and performance on mobile. For actual implementation, Tatyana will look into how to use TensorFlow Lite SDK for pose estimation. Then there will be coverage of Firebase MLKit Base APIs and using custom models with MLKit. Code examples will be in Kotlin. After attending this talk, you will understand the capabilities and limitations of each of these frameworks. You will have a good idea of where to start, what is necessary to implement your ML idea in your app, and potential issues to be aware of.

Password Unlock tut4dl

Protected Area

This content is password-protected. Please verify with a password to unlock the content.

If any links die or problem unrar, send request to

About WoW Team

I'm WoW Team , I love to share all the video tutorials. If you have a video tutorial, please send me, I'll post on my website. Because knowledge is not limited to, irrespective of qualifications, people join hands to help me.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.