Buy Now AED 170.99 + VAT

Monthly Subscription Starting at AED 99 + VAT

Browser-based Models with TensorFlow.js
  • Level Professional
  • المدة 19 ساعات hours
  • الطبع بواسطة DeepLearning.AI
  • Offered by

عن

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this first course, you'll train and run machine learning models in any browser using TensorFlow.js. You'll learn techniques for handling data in the browser, and at the end you'll build a computer vision project that recognizes and classifies objects from a webcam. This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

الوحدات

Specialization Introduction

    • 1 Videos
Show info about module content

1 Videos

  • Specialization Introduction, A Conversation with Andrew Ng

Training and Inference using TensorFlow.js in JavaScript

    • 5 Videos
    • 4 Readings
    • 1 ExternalTool
    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz 1

1 External Tool

  • Intake Survey

5 Videos

  • Course Introduction, A Conversation with Andrew Ng
  • A Few Words From Laurence
  • Building the Model
  • Training the Model
  • First Example In Code

4 Readings

  • Getting Your System Ready
  • Downloading the Ungraded Labs and Programming Assignments
  • [IMPORTANT] Have questions, issues or ideas? Join our Forum!
  • Your First Model

Training Models with CSV Files

    • 5 Videos
    • 4 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • One-Hot Encoding

5 Videos

  • The Iris Dataset
  • Reading the Data
  • One-hot Encoding
  • Designing the NN
  • Iris Classifier In Code

4 Readings

  • Iris Dataset Documentation
  • Using the Web Server
  • Iris Classifier
  • Week 1 Wrap up

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 1

Graded Exercise - Breast Cancer Classification

    • 1 Programming
Show info about module content

1 Programming

  • Week 1 - Breast Cancer Classification

Creating Convolutional Neural Networks in JavaScript

    • 3 Videos
    • 1 Readings
Show info about module content

3 Videos

  • Introduction, A Conversation with Andrew Ng
  • Creating a Convolutional Net with JavaScript
  • Visualizing the Training Process

1 Readings

  • tfjs-vis Documentation

Using a Sprite Sheet

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • What Is a Sprite Sheet?
  • Using the Sprite Sheet

1 Readings

  • MNIST Sprite Sheet

MNIST Classifier

    • 3 Videos
    • 2 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 2 Quiz

3 Videos

  • Using tf.tidy() to Save Memory
  • A Few Words From Laurence
  • MNIST Classifier In Code

2 Readings

  • MNIST Classifier
  • Week 2 Wrap up

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 2

Graded Exercise- Fashion MNIST Classifier

    • 1 Readings
    • 1 Programming
Show info about module content

1 Programming

  • Week 2 - Fashion MNIST Classifier

1 Readings

  • Exercise Description

Toxicity Classifier

    • 5 Videos
    • 2 Readings
Show info about module content

5 Videos

  • Introduction, A Conversation with Andrew Ng
  • A Few Words From Laurence
  • Pre-trained TensorFlow.js Models
  • Toxicity Classifier
  • Toxicity Classifier In Code

2 Readings

  • Important Links
  • Toxicity Classifier

Image Classification Using MobileNet

    • 4 Videos
    • 2 Readings
Show info about module content

4 Videos

  • MobileNet
  • Using MobileNet
  • Training Results
  • MobileNet Example In Code

2 Readings

  • Classes Supported by MobileNet
  • Image Classification Using MobileNet

Converting Models to JSON Format

    • 3 Videos
    • 2 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 3 Quiz

3 Videos

  • Converting Models to JavaScript
  • Converting Models to JavaScript In Code
  • Linear Example In Code

2 Readings

  • Linear Model
  • Week 3 Wrap up

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 3

Graded Exercise - Converting a Python Model to JavaScript

    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Week 3 - Converting a Python Model to JavaScript

1 Labs

  • Week 3: Converting a Python Model to JavaScript

Retraining the MobileNet Model

    • 5 Videos
Show info about module content

5 Videos

  • Introduction, A Conversation with Andrew Ng
  • A Few Words From Laurence
  • Building a Simple Web Page
  • Retraining the MobileNet Model
  • The Training Function

Capturing the Data

    • 3 Videos
Show info about module content

3 Videos

  • Capturing the Data
  • The Dataset Class
  • Training the Network with the Captured Data

Performing Inference From the Webcam Feed

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 4 Quiz

2 Videos

  • Performing Inference
  • Rock Paper Scissors In Code

1 Readings

  • Rock Paper Scissors

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 4

End of Access to Lab Notebooks

    • 1 Readings
Show info about module content

1 Readings

  • [IMPORTANT] Reminder about end of access to Lab Notebooks

Graded Exercise - Rock Paper Scissors

    • 1 Readings
    • 1 Programming
Show info about module content

1 Programming

  • Week 4 - Rock Paper Scissors

1 Readings

  • Exercise Description

Course 1 Wrap up

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • A Conversation with Andrew Ng

1 Readings

  • Wrap up

Auto Summary

"Browser-based Models with TensorFlow.js" is an engaging course for IT and Computer Science professionals. Led by Coursera, this course teaches you to train and run machine learning models directly in the browser using TensorFlow.js. You'll learn data handling techniques and complete a computer vision project. With a duration of approximately 19 hours, it's perfect for those with a foundational knowledge of TensorFlow. Subscription options include a Starter plan. Ideal for learners aiming to enhance their deployment skills and practical ML application.

Laurence Moroney
Instructor

Laurence Moroney