Coursera Project Network
Image Compression and Generation using Variational Autoencoders in Python
Coursera Project Network

Image Compression and Generation using Variational Autoencoders in Python

Taught in English

Ari Anastassiou

Instructor: Ari Anastassiou

3,760 already enrolled

Included with Coursera Plus

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Intermediate level

Recommended experience

90 minutes
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.7

(76 reviews)

What you'll learn

  • How to preprocess and prepare data for vision tasks using PyTorch

  • What a variational autoencoder is and how to train one

  • How to compress, reconstruct, and generate new images using a generative model

Details to know

Shareable certificate

Add to your LinkedIn profile

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Intermediate level

Recommended experience

90 minutes
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.7

(76 reviews)

See how employees at top companies are mastering in-demand skills

Placeholder

Learn, practice, and apply job-ready skills in less than 2 hours

  • Receive training from industry experts
  • Gain hands-on experience solving real-world job tasks
  • Build confidence using the latest tools and technologies
Placeholder

About this Guided Project

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. An introduction to the variational autoencoder and our project

  2. Dataset visualization and preprocessing

  3. Dataset split into training and validation sets

  4. Use data loaders to handle memory overload

  5. Create VAE architecture

  6. Create training loop for VAE

  7. Results of our model and short introduction to other potential projects using a VAE

Recommended experience

Familiarity with machine learning principles is useful. An intermediate level understanding of Python is recommended.

6 project images

Instructor

Instructor ratings
4.5 (5 ratings)
Ari Anastassiou
Coursera Project Network
10 Courses34,084 learners

Offered by

How you'll learn

  • Skill-based, hands-on learning

    Practice new skills by completing job-related tasks.

  • Expert guidance

    Follow along with pre-recorded videos from experts using a unique side-by-side interface.

  • No downloads or installation required

    Access the tools and resources you need in a pre-configured cloud workspace.

  • Available only on desktop

    This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

Showing 3 of 76

4.7

76 reviews

  • 5 stars

    81.57%

  • 4 stars

    10.52%

  • 3 stars

    2.63%

  • 2 stars

    2.63%

  • 1 star

    2.63%

AF
5

Reviewed on Jul 28, 2020

DB
5

Reviewed on May 28, 2020

AS
5

Reviewed on Jun 19, 2020

New to Machine Learning? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions