"Don't touch the poison ivy. We are aware the children's walking trail has numerous poison ivy plants next to the trail, please don't touch the poison ivy."

That sign is on a kids walking trail at a park in Virginia. I stopped dead in my tracks when I read it. 

You can't make this stuff up.

I walk on that trail and I'm always very careful not to touch the poison ivy.

It must be poison ivy, there's a sign that says it's poison ivy, and it's got three leaves. 

Except I saw berries growing on it. Berries don't grown on poison ivy.

What gives?

I couldn't help myself so I turned to Google Lens (thanks Google, love that tool) and it turns out, it's a berry plant that looks just like poison ivy.

Don't trust everything you read.

If you want to learn JAX (and we think you should) you shouldn't trust everything you read.
Turn to a source you trust.

Introducing our newest course, Machine Learning with Google JAX for Python, where you'll dive deep into the high-performance numerical computation library, JAX.

Developed by Google, JAX is gaining rapid popularity in the machine learning and computer vision communities.
Image

Are you interested in learning Machine Learning with Google JAX for Python?
If so, this is your chance!

We are offering a one-time only class that will teach you the basics of JAX and how to use it for machine learning.

The class will be held over four weeks, starting on May 15th and ending on June 9th.

Each week, you will learn a new concept and complete a lesson. You will also have the opportunity to interact with your classmates and ask questions.

This is our first ever cohort based class.
You will have access to a private PyImageSearch Community where you can learn, share, and grow with your fellow students and your instructors.

Join us for a live lesson in week four of our course!

Week four of our course will feature a live lesson with never-before-seen content. This is the first time we've ever done a live lesson for one of our courses, and we're really excited to share this exclusive content with you.

In the live lesson, we'll be covering how to apply JAX skills to build your own deep learning for computer vision model in Python. This is a cutting-edge topic, and we're confident that you'll find the content to be both informative and engaging.

Even if you can't make it to the live lesson, don't worry - you'll still be able to access the recording. We'll make sure to post the recording inside of the class shortly after the live lesson takes place.

Unlike other learning platforms, you will have access to your community after the course ends.

What does that mean?

You will have access to your fellow students, the material, and previous course challenges after your cohort ends. 

The class is open to everyone, regardless of your experience level. We have a diverse group of students from all over the world, so you will have the chance to learn from and connect with people from different backgrounds.

We understand that some people have busy schedules, so we offer a flexible learning option. If you are unable to complete the lessons at the same time as the rest of the class, you can still join the cohort and complete the class at your own pace.

For a limited time, we're offering a 25% discount on our Machine Learning with Google JAX for Python course. But hurry, this offer ends soon!

Why enroll in this course?

  • Comprehensive curriculum covering JAX installation, numerical computation, and machine learning
  • Gain hands-on experience using JAX's powerful features
  • Access to custom curated datasets and an exclusive lesson available only inside the course

By the end of this course, you'll have the skills to use JAX for a variety of tasks, join the growing community of JAX users, and contribute to the development of this exciting technology.

Why should you care about JAX?

Train faster, iterate more!

Our course dives deep into JAX's powerful features like JIT, VMAP, and PMAP, helping you unlock the true potential of computer vision applications.

  • With JIT, you can significantly speed up your code execution
  • VMAP enables efficient vectorization, allowing you to write concise and efficient code
  • PMAP allows for seamless parallelization across multiple devices.

Don't miss this opportunity to enhance your Python skills and gain a competitive edge in the world of machine learning and computer vision. Enroll today and save 25% on the regular price!

Remember, this special offer ends soon, so don't delay.
Register now and take the first step toward mastering Google JAX for Python.

Bonuses!
We have included 2 massive bonuses for all students who join this course.

  1. Custom curated dataset access
  2. Never-before-seen lesson showing machine learning using JAX.

Image

See you in class!

Reserve your spot now and start mastering JAX!

Best regards,
Your PyImageSearch Team

optout