- [Instructor] Since we have done all the preliminary work … in Watson to create our model, and select the data, … we are ready to do the training. … To do that, I want to specify what we're trying to predict. … In this case, it is how likely they … are to vote on the budget. … So under the Select Label column for the column … Value to Predict, we're going to click it down, … and click on adoption of the budget resolution. … We can also select what columns to use to train the dataset. … So we're going to go to Feature Columns … and I'm going to select party, and also el-savalvador-aid, … religious-groups-in-schools, and mix-missile, … how they voted on the immigration bill, … education-spending, and crime. … We have a couple statistical models we can select here. … Because we want we want to predict a yes/no result, … we'll select Binary Classification. … We also see a slider for training, testing, … and hold out data: training data is what is used … to create the model; test data is kept apart …
- 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
- 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.