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Complete iOS 11 Machine Learning Masterclass

Course Summary

Ready to start building professional, career-boosting mobile apps? We sure hope so. Machine learning is one of the fastest growing fields in tech and many apps are starting to integrate machine learning to add a layer of intelligence. Only the smart will survive. In this comprehensive course, you'll learn how to build apps for the brand new iOS 11 while incorporating machine learning, turning them into smart apps that will interact and learn from users to enhance the user experience. Access 86 lectures & 6.5 hours of content 24/7 Explore the three fundamental branches of applied machine learning: image & video processing, text analysis, & speech & language recognition Learn how to apply machine learning to real projects Perform image recognition in an app by differentiating between people & objects, & classifying flowers Add Siri Voice into your app Find trained machine learning models & make them ready to use in iOS apps Receive in-class support


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    Course Syllabus

    • About this course
    • Optional - iOS Fundamentals
    • Optional - Machine Learning Concepts
    • iOS Machine Learning With Photos
    • coreML All about custom models
    • CoreML with Data Set models
    • Project: coreML with Video Camera
    • Section 8: END: iOS coreML fundamentals
    • Optional - Going the extra mile
    • Optional - Numerous Model Conversions
    • Advanced Vision Techniques: Face Detection
    • Advanced Face and Features Detection
    • Advanced - Text Detection
    • About this course
    • Optional - iOS Fundamentals
    • Optional - Machine Learning Concepts
    • iOS Machine Learning With Photos
    • coreML All about custom models
    • CoreML with Data Set models
    • Project: coreML with Video Camera
    • Section 8: END: iOS coreML fundamentals
    • Optional - Going the extra mile
    • Optional - Numerous Model Conversions
    • Advanced Vision Techniques: Face Detection
    • Advanced Face and Features Detection
    • Advanced - Text Detection


Course Fee:
USD 25

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

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