- [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
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
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.