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    • Google Artificial Intelligence for JavaScript Developers with TensorFlow JavaScript

    Google Artificial Intelligence for JavaScript Developers with TensorFlow JavaScript

    BY
    Google via Edx

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    Lavel

    Beginner

    Mode

    Online

    Duration

    7 Weeks

    Fees

    Free

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based
    Learning efforts 3-4 Hours Per Week

    Course and certificate fees

    Type of course

    Free

    certificate availability

    Yes

    certificate providing authority

    Google

    The syllabus

    Module 1

    Welcome to TensorFlow.js
    • Course overview and how people are applying skills you will learn 
    • Who is the course aimed at 
    • Introduce yourself 
    • What will you be making? 
    • Your background

    Module 2

    Introduction to ML & TensorFlow.js
    • What's the difference - AI / ML / Deep Learning 
    • Demystifying Machine Learning 
    • Test your knowledge 
    • What is TensorFlow.js 
    • Three ways to use ML 
    • Test your knowledge

    Module 3

    Using Pre-Made models
    • What are pre-made models? 
    • Selecting the right model to use 
    • Quiz 
    • Case study - using a pre-made model for object detection 
    • Make your own smart security camera 
    • Loading saved TensorFlow.js models directly 
    • Tensors in Tensors out 
    • Coding practice

    Module 4

    Writing custom models
    • Rolling your own models 
    • Starting simple: Predicting a number 
    • Going deeper: Perceptrons 
    • Using a perceptron to predict numbers 
    • Implementing a perceptron for linear regression 
    • Test your knowledge 
    • Going deeper: Multi-layered perceptron 
    • Implementing a multi-layered perceptron 
    • Training a multi layered perceptron for classification task 
    • Test your knowledge 
    • Beyond perceptrons 
    • Researching other ML architecture types

    Module 5

    Transfer Learning
    • Reusing existing models 
    • Make Teachable Machine yourself 
    • Project ideas 
    • Test your knowledge

    Module 6

    Reusing models from Python
    • Benefits of model reuse 
    • Converting Python saved models6.10 Test knowledge 
    • Convert a model yourself 
    • Comment Spam detection 
    • Choosing an appropriate model 
    • Use converted model to check spam in real application 
    • Dealing with edge cases 
    • Retraining a model to deal with custom edge cases

    Module 7

    What models would you convert?
    • To the future and beyond 
    • Machine Learning as a Web Engineer 
    • Find a friend to continue hacking 
    • Course summary and how to join the TensorFlow.js community

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