- [Instructor] IBM's Watson is full-featured machine learning offering. Watson was one of the first machine learning products that really made machine learning accessible and in many ways, is the most mature. A lot of work has been done with Watson to make machine learning simple. For some standard machine learning tasks, they have multiple products. Many of these offerings can be used with very little configuration with pre-made models. The natural language understanding, speech to text, text to speech, and language translator products all fall into this category. IBM Watson's offerings also have something that make general machine learning more accessible to those of us for whom it is not our normal job, a visual designer for models called Watson Studio. With it, creating custom models from whole cloth has been made as simple as possible. From the wizard-type approach to a drag and drop type designer, they are all part of Watson Studio. The Watson Assistant is another offering for the creation of chat bots. It allows developers to create the full flow of chat bots using a visual designer and a minimum amount of code and snippets. All in all, IBM Watson is a great example of what server-side machine learning can be, easy to use for non-data scientists, accessible by developers, but also providing services for data scientists who may need to create very complex models. This URL is a primary IBM Watson Portal. We can use it to set up a new trial account if we don't already have one. If you don't have such a trial account, you should create it now and log in. For one of the services around natural language recognition, we will need to include a credit card for a pay-as-you-go-type account. Luckily the first time you set up this type of account, you will get some dollars and compete hours for free. These should be more than enough to get us through the course.
- 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
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