A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise

Key Features
Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications.
Dive into practical exercises and realworld applications, accompanied by detailed code walkthroughs in Python.
Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings.

Book Description
Mastering Large Language Models with Python is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AIdriven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both opensource and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a wellrounded understanding of LLM implementation.

Through realworld case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AIdriven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence.

What you will learn
Indepth study of LLM architecture and its versatile applications across industries.
Harness opensource and proprietary LLMs to craft innovative solutions.
Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition.
Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage.

Who is This Book For?
This book is tailored for software engineers, data scientists, AI researchers, and technology leaders with a foundational understanding of machine learning concepts and programming. It's ideal for those looking to deepen their knowledge of Large Language Models and their practical applications in the field of AI. If you aim to explore LLMs extensively for implementing inventive solutions or spearheading AIdriven projects, this book is tailored to your needs.

Raj Arun is a distinguished expert in Artificial Intelligence and Data Science, with over fifteen years of industry experience. He holds an MBA from the Indian Institute of Management, Tiruchirapalli, and specialized diplomas in blockchain technology from the Indian Institute of Technology in Madras and Guwahati. Raj is also certified as a quantum Qiskit developer from IBM, marking him as a versatile professional who bridges the gap between traditional computing and quantum advancements.

Throughout his career, Raj has worked in software engineering and development big data, DevOps, and, more recently, the nuanced field of Generative AI. He believes in using technology as a powerful tool for the greater good, aiming at benefiting humanity through creativity and innovation.

Raj's expertise is not confined to a single industry; he has made significant contributions across both B2B and B2C verticals, demonstrating a unique blend of thought leadership and handson skills and delivering scalable and innovative solutions. His approach to AI, viewing it as a semantic layer that seamlessly connects the physical with the virtual, has the potential to create profound societal impacts.

In addition to his professional pursuits, Raj is an ardent supporter of opensource initiatives, contributing his knowledge and expertise to foster a collaborative environment. He is deeply invested in mentoring, guiding both students and professionals alike, and sharing his insights while also learning from the community in return.

His dedication to Responsible AI is evident in his work, ensuring that AIaugmented products and services are ethical, fair, and unbiased.

Raj Arun envisions a future where Generative AI acts as a great equalizer, providing universal access to resources and opportunities and advocates for inclusiveness, empathy, and compassion. Through his work and vision, Raj continues to push the boundaries of possibility, leveraging technology to create a more inclusive, resourceful, and connected world.

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Dr. Deborah Dahl is an expert in Conversational AI and related standards, with over 30 years of experience in the major technical approaches to natural language processing, including Large Language Models. Dr. Dahl focuses on innovative, practical, and scalable conversational AI applications that push the boundary between theory and practice. Her customers range from small startups to large government agencies, seeking out her expertise in applying conversational AI technologies in novel and pioneering applications. Reflecting her interest in standards and interoperability of conversational systems, she currently serves as the Senior Advisor for the Open Voice Interoperability Initiative of the Linux Foundation AI and Data Foundation. In this role, she leads efforts to develop standards for interoperable messaging between conversational AI systems. Dr. Dahl is also a Cochair of the World Wide Web Consortium Voice Interaction Community Group. She has written many technical papers and four books, including Multimodal Interaction with W3C Standards: Toward Natural User Interfaces to Everything, published in 2016, and Natural Language Understanding with Python, published in 2023.

Rohan Chikorde, a seasoned Data Science expert with a decade of experience, specializes in Machine Learning, Large Language Models, and AI. Currently, he serves as an AI Architect at Zensar Technologies, fostering innovation through his technical and leadership skills. His career spans multinational corporations and startups, enhancing his understanding of diverse business applications and honing his skills in advanced machine learning models. A postgraduate in Machine Learning and AI, Rohan is proficient in R, Python, Azure, AWS, GCP, Machine Learning, Deep Learning, AI, DevOps pipelines, LLMs, SQL, Spark, and more. He excels in communicating complex concepts effectively, transforming technical insights into strategic decisions, and mentoring. His expertise spans various domains, and he has a natural flair for leadership. Rohan is recognized as a rising star in the Data Science industry by Digital Vidya. He is open to AI and Data Science management opportunities and can be reached at rohan.chikorde@gmail.com.

Pratik Kotian is an accomplished professional with 8 years of extensive expertise in Natural Language Processing (NLP), Machine Learning (ML), Generative AI, and Python programming. Hailing from Mumbai, India, Pratik has dedicated his career to advancing the frontiers of AI technology and its applications. Pratiks delved into the realm of AI during his academic years, focusing on neural networks. Since then, he has designed and implemented cuttingedge solutions for dataintensive enterprise applications, both onpremises and in the cloud. His passion for integrating AI and ML into these applications has been a driving force throughout his career. With experience across various sectors, including technology, telecommunications, finance, retail, and more, Pratik has honed his skills in leadership roles in research and development, technical consultancy, and team management. Currently, Pratik serves as a Manager at Deloitte, where he leads the Generative AI Team with a focus on pioneering innovative solutions for clients. He drives transformative initiatives, enabling businesses to unlock value through AIdriven strategies. Pratik is dedicated to building and nurturing highperforming teams of experts to support organizational goals. In his spare time, Pratik remains actively engaged in the AI community, sharing knowledge and contributing to advancements in the field. His passion for AIs potential makes him a valued leader in the domain.