- [Narrator] As you work with machine learning … one thing you will come to accept is ambiguity. … Like us machine learning algorithms are evaluating the data … that it is looking at and uses past information … to make a judgment on an answer. … Sometimes it is very sure of the answer, … sometimes it is not. … For example, when looking at messy handwriting … you may think you understand what is written there, … but are not certain. … When working with machine-learning tools … they have the same difficulty … and usually represent that certainty as a percentage. … If an image recognition algorithm states … that it's 74% certain … that it is a picture of a cat … it is up to you as the application developer … to decide if 74% is enough certainty … to assume that the picture is indeed of a cat. … There are several machine-learning technologies … and frameworks that are out there for us to use in our apps. … But they are not all created equal, … that is to say some of them … are geared towards data scientists …
- 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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