- [Instructor] Here we are on the IBM cloud dashboard. … The first Watson machine learning offering … we're going to work with is one for … natural language recognition. … They have a couple of possible services to choose from. … Let's take a look at what there is, … so we're going to start off … by going up to the hamburger menu in the upper left, … and scroll down, and click on Watson. … And then we'll go over the right, and select … Browse all Watson services. … One option is the Watson Assistant. … This includes natural language but is also a framework … to create a complete bot. … Another option is Natural Language Understanding. … This is a pre-trained, general use service. … The final option is the Natural Language Classifier. … This is a service that is only for … natural language understanding and allows us to train it, … so this is the one we're going to use. … So I'm going to go over and click on it. … And it is a paid service, … and we'll need a pay as you go account. … And we're going to change the name on it, …
- 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.