Intermediate Level Technical AI Book Recommendations

For those with some Cloud experience and eager to delve into the world of Generative AI, the following top three AI Book Recommendations offer comprehensive intermediate level training, each focusing on one of the three major cloud platforms; AWS, Azure and GCP. This article recommends the following three new AI Books. If you are an absolute beginner in Generative AI, with some technical experience, you would benefit with 1) Generative AI on AWS (Amazon) and 2) Azure OpenAI Service for Cloud Native Applications (Amazon). These two books will get you setup and running with creating Generative AI Business Applications. On the other hand if you intend to dig a little deeper and read on foundational AI concepts you should try 3) Practical AI on the Google Cloud Platform (Amazon). I would highly recommend the first two books as they will give you some practical skills to get started quickly, on the cloud platform of your choice.

Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications (Amazon)

This book offers a comprehensive guide for professionals looking to leverage generative AI in their businesses. It provides a step-by-step approach to implementing generative AI projects, from defining use cases to deploying models.

Key topics covered include:

• Understanding generative AI: The authors explain different types of generative AI models (LLMs, multimodal models) and their capabilities.

• Project lifecycle: The book outlines the stages involved in a generative AI project, including model selection, fine-tuning, and deployment.

• Practical techniques: Readers will learn about techniques like prompt engineering, in-context learning, and low-rank adaptation for fine-tuning models.

• Ethical considerations: The book addresses the importance of aligning generative AI models with human values through reinforcement learning from human feedback.

• Applications and tools: The authors explore real-world use cases of generative AI and introduce tools like LangChain and ReAct for building AI applications.

• AWS integration: The book specifically focuses on using Amazon Bedrock for implementing generative AI solutions.

Overall, this guide aims to equip professionals with the knowledge and skills needed to effectively harness the power of generative AI for business advantage.

Azure OpenAI Service for Cloud Native Applications: Designing, Planning, and Implementing Generative AI Solutions (Amazon)

This book is ideal for developers and professionals to utilize Azure OpenAI Service to build generative AI applications. It provides a step-by-step approach, covering technical details like setting up Azure resources, working with APIs, and managing costs.

Key topics include:

• Understanding Azure OpenAI Service: The book explains the capabilities of Azure OpenAI Service and its powerful generative AI models like GPT-4.

• Implementation: It guides readers through the process of deploying, customizing, and integrating Azure OpenAI Service with their applications.

• Data management: The book covers how to work with company-owned data to customize large language models and orchestrate knowledge.

• Planning and optimization: It provides insights on planning generative AI projects, estimating costs, and optimizing implementations.

Overall, this guide aims to equip professionals with the knowledge and skills needed to effectively leverage Azure OpenAI Service for building innovative generative AI solutions.

Practical AI on the Google Cloud Platform: Utilizing Google's State-of-the-Art AI Cloud Services (Amazon)

This pick is a slightly Advanced Artificial Intelligence Book, for those inclined to dive deeper and have a preference for the Google Cloud Platform.

This book offers a practical guide for developers looking to leverage Google's AI-powered cloud services. It provides a step-by-step approach to building and training AI models, covering key concepts like data science, machine learning, and deep learning.

Key topics include:

• Understanding Google Cloud AI: The book explains the capabilities of Google Cloud AI services and their applications.

• Building AI models: It guides readers through the process of building and training models using tools like Video AI and AutoML Tables.

• AI applications: The book covers various AI applications, including language processing, image recognition, and chatbot development.

• Practical techniques: Readers will learn about techniques like CNNs, transfer learning, and GANs for building AI models.

Overall, this guide aims to equip developers with the knowledge and skills needed to effectively utilize Google Cloud AI for creating innovative AI solutions.

AI Book Recommendations

The three AI Books recommended in this article offer comprehensive introductions to generative AI on different cloud platforms. If you're already familiar with AWS, Azure, or Google Cloud and want to dive deep into generative AI, the respective books are excellent choices.

For those new to cloud platforms or AI, consider starting with a more general introduction to AI before delving into cloud-specific implementations. Our courses catalog offers a variety of training options, including online courses and workshops, to help you build a solid foundation in AI. Ultimately, the best book for you depends on your platform preference, knowledge level, and specific learning goals.