Affiliate Post ENGINEERING

Course on TensorFlow: Data and Deployment by [Online, 1 Month]: Enroll Now!

By: Rashmi | 15 Jan 2020 11:22 AM

About the Course

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 model.

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, use APIs to control how data splitting, and process all types of unstructured data. 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 AI. 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.

What you will Learn?

  • Run models in your browser using TensorFlow.js
  • Access, organize, and process training data more easily using TensorFlow Data Services
  • Prepare and deploy models on mobile devices using TensorFlow Lite
  • Explore four advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, and TensorBoard

There are 4 Courses in this Specialization

  • Browser-based Models with TensorFlow.js
  • Device-based Models with TensorFlow Lite
  • Data Pipelines with TensorFlow Data Services
  • Advanced Deployment Scenarios with TensorFlow


Laurence Moroney AI Advocate Google Brain

To enroll for this course, click the link below.

Course on TensorFlow: Data and Deployment

Note: Noticebard is associated with Coursera via an affiliate programme.

Get Noticebard’s Posts in Your Email.

Jobs, internships, conferences, scholarships, etc.
Join 38,000 other people!

Related Posts

About the Author


Comment via Facebook

Comment via Website

Your email address will not be published. Required fields are marked *