- [Narrator] We know that model creation … doesn't really happen today on mobile devices, … but that doesn't answer the question … of where should the model run? … Where the model is created, … and the need to access large amounts of data … to create that model in the first place, … really shouldn't be a large deciding factor … with figuring out where the model should run. … When looking at what does matter, … there are several advantages to … running the model server-side. … Server-side machine learning offerings … usually have prebuilt endpoints … to send back information for reinforcement learning. … This makes creating a feedback mechanism … relatively simple for a developer. … Since the model is server-side … and all the evaluation of it takes place on the server, … any reinforcement learning that takes place … to update the model can immediately be used by all clients. … The services also tend to be implemented using rest APIs. … So it really doesn't matter if a client SEK exists or not. …
- Defining machine learning
- Training a machine learning model
- Comparing machine learning frameworks
- Using IBM Watson for mobile machine learning
- Using Azure Machine Learning for speech and image recognition
- Training Core ML models
- Comparing client-side and server-side models
Skill Level Beginner
Xamarin and Android Studio: Material Designwith Kevin Ford1h 47m Intermediate
Machine Learning for iOS Developerswith Brian Advent1h 25m Advanced
1. Introduction to Machine Learning
2. Server Models: IBM Watson
3. Server Models: Azure Machine Learning
4. Client Models: Core ML
5. Understanding the Offerings
Next steps1m 40s
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