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[FreeCoursesOnline.Me] [LYNDA] Machine Learning In Mobile Applications [FCO]
Machine learning is reaching the mainstream. With the new tools available to developers, it's now possible to implement machine learning features—voice, face, and image recognition; personalized recommendations; and more—in a mobile context. This course explores how to apply the power of machine learning to mobile app development, using platforms such as IBM Watson, Microsoft Azure Cognitive Services, and Apple Core ML. Instructor Kevin Ford demos each product, reviewing the different features and approaches to machine learning. He shows how to train and deploy models for natural language and visual recognition and how to generate statistical models for use in a Xamarin application. In chapter five, he compares client-side and server-side models and explains when a developer might choose one platform over another.
Topics include:
• 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.
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FILE LIST
Filename
Size
1.Introduction/01.Machine learning in mobile apps.mp4
10.5 MB
1.Introduction/02.What you should know.mp4
5.6 MB
1.Introduction/03.Using the exercise files.mp4
12.9 MB
2.1. Introduction to Machine Learning/04.What is machine learning.mp4
5.9 MB
2.1. Introduction to Machine Learning/05.Required concepts.mp4
7.3 MB
2.1. Introduction to Machine Learning/06.Why does this matter for my app.mp4
7.4 MB
2.1. Introduction to Machine Learning/07.Training a model.mp4
3.7 MB
2.1. Introduction to Machine Learning/08.Machine learning vs. deep learning.mp4
4.1 MB
2.1. Introduction to Machine Learning/09.What can I do with machine learning.mp4
4.4 MB
2.1. Introduction to Machine Learning/10.Server-side vs. client-side ML.mp4
4.6 MB
2.1. Introduction to Machine Learning/11.ML frameworks.mp4
5.5 MB
3.2. Server Models - IBM Watson/12.Overview of Watson.mp4
4.3 MB
3.2. Server Models - IBM Watson/13.Natural Language Understanding - Set up.mp4
6.5 MB
3.2. Server Models - IBM Watson/14.Natural Language Understanding - Train the model.mp4
12.3 MB
3.2. Server Models - IBM Watson/15.Visual Recognition - Set up.mp4
4.5 MB
3.2. Server Models - IBM Watson/16.Visual Recognition - Train the model.mp4
12 MB
3.2. Server Models - IBM Watson/17.Create a custom model.mp4
12.7 MB
3.2. Server Models - IBM Watson/18.Train and deploy a custom model.mp4
10.1 MB
3.2. Server Models - IBM Watson/19.Install client SDK package.mp4
7.6 MB
3.2. Server Models - IBM Watson/20.Client tie to Natural Language.mp4
21.6 MB
3.2. Server Models - IBM Watson/21.Client tie to Visual Recognition call setup.mp4
22 MB
3.2. Server Models - IBM Watson/22.Client tie to Visual Recognition response.mp4
20.1 MB
3.2. Server Models - IBM Watson/23.Client tie to custom model - Get an access token.mp4
21 MB
3.2. Server Models - IBM Watson/24.Client tie to call custom model service.mp4
30.3 MB
3.2. Server Models - IBM Watson/25.Client tie to get custom model response.mp4
10.5 MB
3.2. Server Models - IBM Watson/26.Run the client app.mp4
9.5 MB
4.3. Server Models - Azure Machine Learning/27.Azure Machine Learning overview.mp4
4.5 MB
4.3. Server Models - Azure Machine Learning/28.Language Understanding - Set up.mp4
6.5 MB
4.3. Server Models - Azure Machine Learning/29.Language Understanding - Intents.mp4
10.1 MB
4.3. Server Models - Azure Machine Learning/30.Language Understanding - Utterances.mp4
9.8 MB
4.3. Server Models - Azure Machine Learning/31.Custom Vision - Set up.mp4
12.6 MB
4.3. Server Models - Azure Machine Learning/32.Machine Learning Studio - Set up.mp4
12.3 MB
4.3. Server Models - Azure Machine Learning/33.Machine Learning Studio - Create model.mp4
9.1 MB
4.3. Server Models - Azure Machine Learning/34.Machine Learning Studio - Publish model.mp4
8.3 MB
4.3. Server Models - Azure Machine Learning/35.Install client SDK package.mp4
5.9 MB
4.3. Server Models - Azure Machine Learning/36.Client tie to LUIS.mp4
17.8 MB
4.3. Server Models - Azure Machine Learning/37.Client tie to Custom Vision model.mp4
17.5 MB
4.3. Server Models - Azure Machine Learning/38.Client tie to custom model.mp4
13.3 MB
4.3. Server Models - Azure Machine Learning/39.Client tie to custom model - Set up request.mp4
22.6 MB
4.3. Server Models - Azure Machine Learning/40.Client tie to custom model - Make the call.mp4
29.6 MB
4.3. Server Models - Azure Machine Learning/41.Run the clent app.mp4
5.9 MB
5.4. Client Models - Core ML/42.Core ML overview.mp4
3.9 MB
5.4. Client Models - Core ML/43.Core ML - Create Natural Language model.mp4
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