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Working in a hands-on learning environment, led by our Machine Learning for Mobile expert instructor, students will learn about and explore: Build smart mobile applications for Android and iOS devices.Use popular machine learning toolkits such as Core ML and TensorFlow Lite.Explore cloud services for machine learning that can be used in mobile apps.

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Unlimited Duration

Last Updated

January 12, 2021

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1

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Certification

Course Curriculum

    • Introduction to Machine Learning on Mobile 00:00:00
    • Definition of machine learning 00:00:00
    • The machine learning process 00:00:00
    • Types of learning 00:00:00
    • Why use machine learning on mobile devices? 00:00:00
    • Supervised and Unsupervised Learning Algorithms 00:00:00
    • Introduction to supervised learning algorithms 00:00:00
    • Deep dive into supervised learning algorithms 00:00:00
    • Introduction to unsupervised learning algorithms 00:00:00
    • Deep dive into unsupervised learning algorithms 00:00:00
    • Random Forest on iOS 00:00:00
    • Introduction to algorithms 00:00:00
    • Solving the problem using random forest in Core ML 00:00:00
    • TensorFlow Mobile in Android 00:00:00
    • An introduction to TensorFlow 00:00:00
    • The architecture of a mobile machine learning application 00:00:00
    • Writing the mobile application using the TensorFlow model 00:00:00
    • Regression Using Core ML in iOS 00:00:00
    • Introduction to regression 00:00:00
    • Understanding the basics of Core ML 00:00:00
    • Solving the problem using regression in Core ML 00:00:00
    • The ML Kit SDK 00:00:00
    • Understanding ML Kit 00:00:00
    • Creating a text recognition app using Firebase on-device APIs 00:00:00
    • Creating a text recognition app using Firebase on-cloud APIs 00:00:00
    • Face detection using ML Kit 00:00:00
    • Spam Message Detection 00:00:00
    • Understanding NLP 00:00:00
    • Understanding linear SVM algorithm 00:00:00
    • Solving the problem using linear SVM in Core ML 00:00:00
    • Fritz 00:00:00
    • Introduction to Fritz 00:00:00
    • Hand-on samples using Fritz 00:00:00
    • Neural Networks on Mobile 00:00:00
    • Introduction to neural networks 00:00:00
    • Image recognition solution 00:00:00
    • Creating a TensorFlow image recognition model 00:00:00
    • Handwritten digit recognition solution 00:00:00
    • Introduction to Keras 00:00:00
    • Installing Keras 00:00:00
    • Solving the problem 00:00:00
    • Mobile Application Using Google Vision 00:00:00
    • Features of Google Cloud Vision 00:00:00
    • Sample mobile application using Google Cloud Vision 00:00:00
    • The Future of ML on Mobile Applications 00:00:00
    • Key ML mobile applications 00:00:00
    • Key innovation areas 00:00:00
    • Opportunities for stakeholders 00:00:00

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