- [Narrator] When creating a model, … you want to use some of our data to train the model … and some to validate the results. … To do that with Azure Machine Learning Studio, … we can go under Data Transformation. … Let's close some of these up, … and under sample and split, … and we see split data, … so we're going to drag that onto the desktop, … and connect that after we selected our columns. … Now here we see that it says the fraction of the rows … in the first node is .5. … We're going to change that to .8, … and what that's going to do is it's going to put 80% of … the data on node one and 20% of it on node two, … and I'll give it a random seed number just to … randomize the data on which goes where a little bit, … and it can just be anything there. … Since we are trying to predict … if they voted yes on a budget, … we need to use the appropriate statistical model. … So we're going to look under … Machine Learning Initialize Model, … and then under classification, … and here we're going to want the two …
- 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
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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