Название: Empowering the Public Sector with Generative AIАвтор: Sanjeev Pulapaka, Srinath Godavarthi, Dr. Sherry Ding
Издательство: Apress
Год: 2024
Страниц: 275
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
This is your guide book to Generative AI (GenAI) and its application in addressing real-world challenges within the public sector. The book addresses a range of topics from GenAI concepts and strategy to public sector use cases, architecture patterns, and implementation best practices. With a general background in technology and the public sector, you will be able to understand the concepts in this book.
The book will help you develop a deeper understanding of GenAI and learn how GenAI differs from traditional AI. You will explore best practices such as prompt engineering, and fine-tuning, and architectural patterns such as Retrieval Augmented Generation (RAG). And you will discover specific nuances, considerations, and strategies for implementation in a public sector organization.
You will understand how to apply these concepts in a public sector setting and address industry-specific challenges and problems by studying a variety of use cases included in the book in the areas of content generation, chatbots, summarization, and program management.
We mentioned several types of algorithms, such as Logistic Regression, Support Vector Machines, Naive Bayes Algorithm, and Neural Networks. Each of these algorithms essentially does the same thing: they use an optimization technique to come up with an ML model that is then used to complete a task or make a prediction. Of these algorithms, Artificial Neural Networks (ANNs) or neural networks have become one of the most researched and used algorithms in ML, so much so that an entire branch of ML called Deep Learning is used to describe tasks that use these algorithms. Neural networks and Deep Learning are some of the fundamental forces driving the rise of AI. Self-driving cars, voice recognition devices such as Alexa, and many current AI-based technologies all use neural networks. Through the last decade, hardware and chips such as Graphical Processing Units (GPUs) have been invented to accelerate the processing of data for Deep Learning tasks. These developments have further propelled the use of Deep Learning into the realms of fields such as GenAI.
What You Will Learn:
GenAI concepts and how GenAI differs from traditional AI/ML
Prompt engineering, fine-tuning, RAG, and customizing foundation models
Strategy, methodologies, and frameworks for the public sector
Public sector use cases in the areas of content generation, summarization, and chatbots, plus program management, analytics, business intelligence, and reporting
Architecture and design patterns
Implementation, operations, and maintenance of GenAI applications
Who This Book Is For:
Technology and business leaders in the public sector who are new to AI/ML and are keen on exploring and harnessing the potential of Generative AI in their respective organizations.
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