- [Instructor] With our Azure services set up, … we can now tie them into our client application. … To do that, we're going to go into the exercise files … folder on our desktop … and go to client project start, right click on it, … and copy it. … And we'll close that window and paste it to the desktop. … Now we'll rename that to Azure project. … And open the folder and double click … on the ML sample solution to open it up in Visual Studio. … We do want to make sure all the NuGet packages are restored … so we're going to right click on ML sample solutions … and go restore NuGet packages. … When that's done, we want to import a few NuGet packages … to make sure connecting to our services is easy. … There are packages available from LUIS … and Custom Vision. … So to start, we're going to open up the ML sample project … and right click on dependencies and go to add packages. … In the search box, we're going to type in Microsoft, … Azure, cognitive services, … and LUIS runtime. … And here it is, so we'll select 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.