About this Course

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Learner Career Outcomes

25%

got a tangible career benefit from this course

33%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

Basic understanding of JavaScript

Approx. 18 hours to complete
English

What you will learn

  • Train and run inference in a browser

  • Handle data in a browser

  • Build an object classification and recognition model using a webcam

Skills you will gain

Convolutional Neural NetworkMachine LearningTensorflowObject DetectionTensorFlow.js

Learner Career Outcomes

25%

got a tangible career benefit from this course

33%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

Basic understanding of JavaScript

Approx. 18 hours to complete
English

Instructor

Offered by

Placeholder

DeepLearning.AI

Syllabus - What you will learn from this course

Content RatingThumbs Up95%(1,599 ratings)Info
Week
1

Week 1

5 hours to complete

Introduction to TensorFlow.js

5 hours to complete
11 videos (Total 30 min), 7 readings, 3 quizzes
11 videos
Course Introduction, A Conversation with Andrew Ng1m
A Few Words From Laurence2m
Building the Model3m
Training the Model3m
First Example In Code4m
The Iris Dataset1m
Reading the Data4m
One-hot Encoding1m
Designing the NN2m
Iris Classifier In Code6m
7 readings
Getting Your System Ready10m
Downloading the Coding Examples and Exercises10m
Your First Model10m
Iris Dataset Documentation10m
Using the Web Server10m
Iris Classifier10m
Week 1 Wrap up10m
2 practice exercises
Quiz 1
One-Hot Encoding
Week
2

Week 2

4 hours to complete

Image Classification In the Browser

4 hours to complete
8 videos (Total 27 min), 5 readings, 2 quizzes
8 videos
Creating a Convolutional Net with JavaScript4m
Visualizing the Training Process2m
What Is a Sprite Sheet?1m
Using the Sprite Sheet2m
Using tf.tidy() to Save Memory1m
A Few Words From Laurence24s
MNIST Classifier In Code13m
5 readings
tjs-vis Documentation10m
MNIST Sprite Sheet10m
MNIST Classifier10m
Week 2 Wrap up10m
Exercise Description10m
1 practice exercise
Week 2 Quiz
Week
3

Week 3

5 hours to complete

Converting Models to JSON Format

5 hours to complete
12 videos (Total 28 min), 7 readings, 2 quizzes
12 videos
A Few Words From Laurence1m
Pre-trained TensorFlow.js Models49s
Toxicity Classifier3m
Toxicity Classifier In Code3m
MobileNet49s
Using MobileNet1m
Training Results1m
MobileNet Example In Code3m
Converting Models to JavaScript4m
Converting Models to JavaScript In Code2m
Linear Example In Code1m
7 readings
Important Links10m
Toxicity Classifier10m
Classes Supported by MobileNet10m
Image Classification Using MobileNet10m
Linear Model10m
Week 3 Wrap up10m
Optional - Install Wget (Only If Needed)10m
1 practice exercise
Week 3 Quiz
Week
4

Week 4

4 hours to complete

Transfer Learning with Pre-Trained Models

4 hours to complete
11 videos (Total 26 min), 3 readings, 2 quizzes
11 videos
A Few Words From Laurence53s
Building a Simple Web Page2m
Retraining the MobileNet Model1m
The Training Function2m
Capturing the Data3m
The Dataset Class2m
Training the Network with the Captured Data1m
Performing Inference4m
Rock Paper Scissors In Code4m
A Conversation with Andrew Ng1m
3 readings
Rock Paper Scissors10m
Exercise Description10m
Wrap up10m
1 practice exercise
Week 4 Quiz

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About the TensorFlow: Data and Deployment Specialization

TensorFlow: Data and Deployment

Frequently Asked Questions

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