FAQs

What is included in a Packt subscription?

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription?

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits?

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled?

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title?

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team.

Can I download the code files for Early Access titles?

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date?

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready?

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access?

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered?

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content?

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access?

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.

H2N Mar 11, 2024

It is for MLOps engineers, DevOps engineers, IT architects, and data scientists interested in MLOps and the Red Hat OpenShift Data Science platform. It introduces MLOps concepts and the Red Hat OpenShift platform, walking readers through provisioning an MLOps platform in the cloud, building machine learning models with OpenShift, managing model training workflows, deploying ML models as a service, and operating ML workloads.

Amazon Verified review

Om S Mar 08, 2024

"MLOps with Red Hat OpenShift" serves as an essential tool for MLOps and DevOps engineers, data experts, and scientists keen on mastering machine learning operations (MLOps) using OpenShift. This book breaks down MLOps into digestible parts, from initial data setup to the final deployment of models, guiding readers through using OpenShift to create effective ML pipelines. It begins with fundamental MLOps concepts, preparing readers with a solid foundation and a clear understanding of OpenShift's basics, such as containers and pods.The journey continues as readers dive into MLOps workflows, exploring the integration of machine learning frameworks for model training and testing. The focus then shifts to the use of Red Hat OpenShift Data Science and partner components like Pachyderm and Intel OpenVino. These tools play critical roles in managing data pipelines and deploying and monitoring machine learning models.Step-by-step instructions ensure that readers can follow along with ease, making the complexities of MLOps workflows manageable and understandable. The book not only educates on building MLOps pipelines for automation but also delves into model serving techniques using advanced tools like Seldon and Intel OpenVino.Targeted at MLOps and DevOps engineers, data architects, and scientists interested in leveraging OpenShift for machine learning, this book is also an invaluable resource for developers eager to learn about MLOps components. It effectively demystifies the process of building scalable and efficient machine learning workflows on the OpenShift platform, offering readers the skills needed for MLOps success.

MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations

What do you get with a Packt Subscription?