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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

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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.

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Amazon verified reviews

Subhasish Ghosh Aug 27, 2024

Just finished perusing "𝑮𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑨𝑰 𝒇𝒐𝒓 𝑪𝒍𝒐𝒖𝒅 𝑺𝒐𝒍𝒖𝒕𝒊𝒐𝒏𝒔: 𝑨𝒓𝒄𝒉𝒊𝒕𝒆𝒄𝒕 𝒎𝒐𝒅𝒆𝒓𝒏 𝑨𝑰 𝑳𝑳𝑴𝒔 𝒊𝒏 𝒔𝒆𝒄𝒖𝒓𝒆, 𝒔𝒄𝒂𝒍𝒂𝒃𝒍𝒆, 𝒂𝒏𝒅 𝒆𝒕𝒉𝒊𝒄𝒂𝒍 𝒄𝒍𝒐𝒖𝒅 𝒆𝒏𝒗𝒊𝒓𝒐𝒏𝒎𝒆𝒏𝒕𝒔", authored by my Microsoft colleagues, Paul S. & Anurag Karuparti, Packt Publications. An excellent read, this is a nicely detailed book for those looking to start your journey into Generative AI.𝐓𝐚𝐫𝐠𝐞𝐭 𝐚𝐮𝐝𝐢𝐞𝐧𝐜𝐞: Aspiring Cloud Architects, Data Analysts, Cloud Dev, Data Scientists, AI Researchers, Tech Business Leaders, and Tech Evangelists.✅ What this book is: Broad high-level overview of GenAI❎ What this book is not: This is not a technical deep dive into Algorithms, Transformer Model variants or Code for LLMs/LMMs/SLMs etc.5 things that makes this book a good read:1️⃣ Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together.2️⃣ Understand how we started applying NLP to concepts like transformers. Grasp the process of fine-tuning and developing apps based on RAG.3️⃣ Explore effective prompt engineering strategies. Acquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIs.4️⃣ Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI.5️⃣ Loved the chapters #4 & #5, which focuses on Retrieval-Augmented Generation (RAG), Vector DB essentials, role it plays in RAG, chunking strategies, KNNs versus ANNs, Azure Prompt Flow, Essential Prompt Engineering techniques and more. These 2 chapters are excellent for those looking to get a solid grasp on both the theoretical and conceptual aspects & practical aspects of RAG & Prompt Engineering.Overall, highly recommended book.

Amazon Verified review

Steven Fernandes May 07, 2024

An indispensable guide for anyone venturing into the world of generative AI and large language models (LLMs). This book offers a comprehensive exploration, from the basic concepts of natural language processing (NLP) and transformers to the nuanced details of fine-tuning and application development using retrieval-augmented generation (RAG). It includes in-depth discussions on prompt engineering, application frameworks, and the lifecycle of LLMs, along with crucial considerations in LLMOps, autonomous agents, and Assistants APIs. Additionally, the book provides practical advice on scaling and securing GenAI systems and emphasizes the principles of responsible AI. A thorough and enlightening read for both novices and experienced practitioners in the field.

homePC Jun 10, 2024

I did not set a high expectation when I started reading, but it was extremely good. I like the approach and the concise way of explaining complicated topics in an easy-to-understand way.

Om S Jun 14, 2024

This book is a brilliant introduction to the integration of cloud computing with generative AI. The chapter 'Cloud Computing Meets Generative AI: Bridging Infinite Impossibilities' really expanded my understanding of the potential in combining these technologies. I found 'NLP Evolution and Transformers' very enlightening, particularly for its deep dive into how NLPs and LLMs are evolving. The 'Fine Tuning' chapter provided practical insights into tailoring AI applications to specific domains. 'RAGs to Riches' introduced an innovative approach to leveraging external data in AI models. The strategies shared in 'Effective Prompt Engineering Strategies' are essential for anyone looking to refine AI outputs. 'Developing and Operationalizing LLM-Based Cloud Applications' was a great guide on the lifecycle of AI apps. The security chapter addressed crucial considerations needed to protect AI systems. 'Responsible Development of AI Solutions' emphasized ethical practices which are vital in AI development. Lastly, 'Future of Generative AI' offered an exciting peek into what the next era of AI might hold.

Jose Arias May 16, 2024

This is a very good and clear book that has helped me understand the fundamentals of generative ai. I love how it starts from scratch and builds up going through all the components.

Generative AI for Cloud Solutions: Architect modern AI LLMs in secure, scalable, and ethical cloud environments

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