About this Course

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Intermediate Level

Basic understanding of JavaScript

Approx. 18 hours to complete
English
Subtitles: 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
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
Subtitles: English

Instructor

Offered by

deeplearning.ai logo

deeplearning.ai

Syllabus - What you will learn from this course

Content RatingThumbs Up95%(1,167 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

Reviews

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About the TensorFlow: Data and Deployment Specialization

Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models. In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more. Industries all around the world are adopting Artificial Intelligence. This Specialization from Laurence Moroney and Andrew Ng will help you develop and deploy machine learning models across any device or platform faster and more accurately than ever. This Specialization builds upon skills learned in the TensorFlow in Practice Specialization. We recommend learners complete that Specialization prior to enrolling in TensorFlow: Data and Deployment....
TensorFlow: Data and Deployment

Frequently Asked Questions

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