# Firebase ML

Published articles for Firebase ML.

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## Using Machine Learning to optimize mobile game experiences

DevFeed: [Using Machine Learning to optimize mobile game experiences](<https://devfeed.tech/articles/using-machine-learning-to-optimize-mobile-game-experiences-16426.md>)

Original publisher: [Read original article](<https://firebase.blog/posts/2022/02/custom-ondevice-machine-learning>)

Author: Sachin Kotwani; Elvis Sun

Published: 2022-02-15T00:00:00Z

Content type: tutorial

Language: en

Sources: [Firebase Blog](<https://devfeed.tech/sources/firebase-blog.md>)

Topics: [Mobile](<https://devfeed.tech/topics/mobile.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [personalization](<https://devfeed.tech/topics/personalization.md>), [Firebase](<https://devfeed.tech/topics/firebase.md>), [Inference](<https://devfeed.tech/topics/inference.md>)

Tags: [firebase](<https://devfeed.tech/tags/firebase.md>), [firebase-ml](<https://devfeed.tech/tags/firebase-ml.md>), [games](<https://devfeed.tech/tags/games.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [mobile](<https://devfeed.tech/tags/mobile.md>), [model](<https://devfeed.tech/tags/model.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [personalization](<https://devfeed.tech/tags/personalization.md>), [tutorials](<https://devfeed.tech/tags/tutorials.md>)

### AI overview

This Firebase tutorial explains how HalfBrick used a custom machine learning model running on-device to personalize rewards in Jetpack Joyride based on player skill and session details. The first experiment increased rewarded-ad conversions by 36%.

### Source excerpt

News, tutorials, and updates from the Firebase team.

## Enhance your TensorFlow Lite deployment with Firebase

DevFeed: [Enhance your TensorFlow Lite deployment with Firebase](<https://devfeed.tech/articles/enhance-your-tensorflow-lite-deployment-with-firebase-16344.md>)

Original publisher: [Read original article](<https://firebase.blog/posts/2020/06/enhance-your-tensorflow-lite-deployment-with-firebase>)

Author: Khanh LeViet

Published: 2020-06-26T00:00:00Z

Content type: tutorial

Language: en

Sources: [Firebase Blog](<https://devfeed.tech/sources/firebase-blog.md>)

Topics: [Firebase](<https://devfeed.tech/topics/firebase.md>), [TensorFlow Lite](<https://devfeed.tech/topics/tensorflow-lite.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [Firebase ML](<https://devfeed.tech/topics/firebase-ml.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Mobile](<https://devfeed.tech/topics/mobile.md>)

Tags: [android](<https://devfeed.tech/tags/android.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [firebase](<https://devfeed.tech/tags/firebase.md>), [firebase-ml](<https://devfeed.tech/tags/firebase-ml.md>), [google](<https://devfeed.tech/tags/google.md>), [inference](<https://devfeed.tech/tags/inference.md>), [ios](<https://devfeed.tech/tags/ios.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml-kit](<https://devfeed.tech/tags/ml-kit.md>), [remote-config](<https://devfeed.tech/tags/remote-config.md>), [tensorflow-lite](<https://devfeed.tech/tags/tensorflow-lite.md>)

### AI overview

This tutorial explains how to use Firebase Machine Learning to enhance TensorFlow Lite model deployment in Android and iOS applications. It covers over-the-air model delivery, downloading models on demand, model management through the Firebase Console or API, and production features such as inference-speed measurement and A/B testing.

### Source excerpt

News, tutorials, and updates from the Firebase team.