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Solutions Architect's Handbook

Solutions Architect's Handbook

By : Saurabh Shrivastava, Neelanjali Srivastav
4.7 (59)
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Solutions Architect's Handbook

Solutions Architect's Handbook

4.7 (59)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Master the art of solution architecture and excel as a Solutions Architect with the Solutions Architect's Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. Large language models, generative AI, and innovations in deep learning are cutting-edge advancements shaping the future of technology. Topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient and secure architectures remain important in today's landscape. This book provides coverage of these emerging and key technologies and walks you through solution architecture design from key principles, providing you with the knowledge you need to succeed as a Solutions Architect. It will also level up your soft skills, providing career-accelerating techniques to help you get ahead. Unlock the potential of cutting-edge technologies, gain practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.
Table of Contents (20 chapters)
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18
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19
Index

NLP

NLP aims to understand and read, as well as utilize, the human language well. It combines AI and computational linguistics so that computers can process human language through spoken words or text. Let’s look at some of the use cases of NLP.

Chatbots and virtual assistants

One of the common applications of NLP is in creating chatbots and virtual assistants like Siri, Alexa, or customer service chatbots on various websites.

Chatbots engage in interactive conversations with users, often assisting them in finding information, answering queries, or facilitating transactions. They leverage NLP to understand user inputs (questions or commands) and generate relevant responses. By analyzing the text, NLP models discern the intent behind the user’s message and respond accordingly. This application is widely utilized across industries like retail, banking, and customer service to enhance user experience and provide immediate responses to customer inquiries.

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