Large Language Model-Based Solutions PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Large Language Model-Based Solutions PDF full book. Access full book title Large Language Model-Based Solutions by Shreyas Subramanian. Download full books in PDF and EPUB format.
Author: Shreyas Subramanian
Publisher: John Wiley & Sons
ISBN: 1394240732
Category : Computers
Languages : en
Pages : 322
Get Book
Book Description
Learn to build cost-effective apps using Large Language Models In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning. The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find: Effective strategies to address the challenge of the high computational cost associated with LLMs Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models Perfect for developers and data scientists interested in deploying foundational models, or business leaders planning to scale out their use of GenAI, Large Language Model-Based Solutions will also benefit project leaders and managers, technical support staff, and administrators with an interest or stake in the subject.
Author: Shreyas Subramanian
Publisher: John Wiley & Sons
ISBN: 1394240732
Category : Computers
Languages : en
Pages : 322
Get Book
Book Description
Learn to build cost-effective apps using Large Language Models In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning. The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find: Effective strategies to address the challenge of the high computational cost associated with LLMs Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models Perfect for developers and data scientists interested in deploying foundational models, or business leaders planning to scale out their use of GenAI, Large Language Model-Based Solutions will also benefit project leaders and managers, technical support staff, and administrators with an interest or stake in the subject.
Author: Sanket Subhash Khandare
Publisher: BPB Publications
ISBN: 9355519656
Category : Computers
Languages : en
Pages : 465
Get Book
Book Description
Do not just talk AI, build it: Your guide to LLM application development KEY FEATURES ● Explore NLP basics and LLM fundamentals, including essentials, challenges, and model types. ● Learn data handling and pre-processing techniques for efficient data management. ● Understand neural networks overview, including NN basics, RNNs, CNNs, and transformers. ● Strategies and examples for harnessing LLMs. DESCRIPTION Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks , and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. WHAT YOU WILL LEARN ● Grasp fundamentals of natural language processing (NLP) applications. ● Explore advanced architectures like transformers and their applications. ● Master techniques for training large language models effectively. ● Implement advanced strategies, such as meta-learning and self-supervised learning. ● Learn practical steps to build custom language model applications. WHO THIS BOOK IS FOR This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP). TABLE OF CONTENTS 1. Fundamentals of Natural Language Processing 2. Introduction to Language Models 3. Data Collection and Pre-processing for Language Modeling 4. Neural Networks in Language Modeling 5. Neural Network Architectures for Language Modeling 6. Transformer-based Models for Language Modeling 7. Training Large Language Models 8. Advanced Techniques for Language Modeling 9. Top Large Language Models 10. Building First LLM App 11. Applications of LLMs 12. Ethical Considerations 13. Prompt Engineering 14. Future of LLMs and Its Impact
Author: Xiangyu Song
Publisher: Springer Nature
ISBN: 9819729912
Category :
Languages : en
Pages : 95
Get Book
Book Description
Author: Ilias Maglogiannis
Publisher: Springer Nature
ISBN: 3031341112
Category : Computers
Languages : en
Pages : 606
Get Book
Book Description
This two-volume set of IFIP-AICT 675 and 676 constitutes the refereed proceedings of the 19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023, held in León, Spain, during June 14–17, 2023. This event was held in hybrid mode. The 75 regular papers and 17 short papers presented in this two-volume set were carefully reviewed and selected from 185 submissions. The papers cover the following topics: Deep Learning (Reinforcement/Recurrent Gradient Boosting/Adversarial); Agents/Case Based Reasoning/Sentiment Analysis; Biomedical - Image Analysis; CNN - Convolutional Neural Networks YOLO CNN; Cyber Security/Anomaly Detection; Explainable AI/Social Impact of AI; Graph Neural Networks/Constraint Programming; IoT/Fuzzy Modeling/Augmented Reality; LEARNING (Active-AutoEncoders-Federated); Machine Learning; Natural Language; Optimization-Genetic Programming; Robotics; Spiking NN; and Text Mining /Transfer Learning.
Author: Abhivardhan
Publisher: BPB Publications
ISBN: 9355516223
Category : Computers
Languages : en
Pages : 178
Get Book
Book Description
Unveiling the future: Navigating AI's Intricate Intersection with International Law – A Journey Beyond Hype and Governance KEY FEATURES ● Comprehensive overview of AI ethics and international law. ● Exploration of pragmatic approaches to AI governance. ● Navigation of global legal dynamics. ● Soft law recommendations for responsible AI development. DESCRIPTION Dive into the dynamic realm of AI governance with this groundbreaking book. Offering cutting-edge insights, it explores the intricate intersection of artificial intelligence and international law. Readers gain invaluable perspectives on navigating the evolving AI landscape, understanding global legal dynamics, and delving into the nuances of responsible AI governance. Packed with pragmatic approaches, the book is an essential guide for professionals, policymakers, and scholars seeking a comprehensive understanding of the multifaceted challenges and opportunities presented by AI in the global legal arena. The book begins by examining the fundamental concepts of AI ethics and its recognition within international law. It then delves into the challenges of governing AI in a rapidly evolving technological landscape, highlighting the need for pragmatic and flexible approaches to AI regulation. Subsequent chapters explore the diverse perspectives on AI classification and recognition, from legal visibility frameworks to the ISAIL Classifications of Artificial Intelligence. The book also examines the far-reaching implications of Artificial General Intelligence (AGI) and digital colonialism, addressing the ethical dilemmas and potential dangers of these emerging technologies. In conclusion, the book proposes a path toward self-regulation and offers soft law recommendations to guide the responsible development and deployment of AI. It emphasizes the importance of international cooperation and collaboration in addressing the ethical and legal challenges posed by AI, ensuring that AI's transformative power is harnessed for the benefit of all humanity. WHAT YOU WILL LEARN ● Understand AI's impact on global legal frameworks. ● Navigate complexities of AI governance and responsible practices. ● Explore innovative AI applications and economic dimensions. ● Grasp legal visibility, privacy doctrines, and classification methods. ● Assess the evolution from Narrow AI to AGI and digital colonialism. ● Gain insights into self-regulation and the future of AI. WHO THIS BOOK IS FOR This book is tailored for professionals, policymakers, and scholars seeking a comprehensive understanding of AI's intersection with international law. While no specific prerequisites are necessary, a foundational awareness of AI concepts and legal frameworks will enhance the reader's engagement with the material. TABLE OF CONTENTS SECTION 1: Introduction 1. Artificial Intelligence and International Law SECTION 2: Technology Governance 2. Pragmatism in Governing AI 3. The Innovation and Economics of AI SECTION 3: Classification and Recognition of Artificial Intelligence 4. Legal Visibility 5. The Privacy Doctrine 6. The ISAIL Classifications of Artificial Intelligence SECTION 4: Artificial Intelligence in a Multi-polar World 7. AGI and Digital Colonialism 8. Self-Regulating the Future of AI
Author: Mourad Abbas
Publisher: Springer Nature
ISBN: 3031442601
Category : Technology & Engineering
Languages : en
Pages : 145
Get Book
Book Description
This book unveils the most advanced techniques and innovative applications in the natural language processing (NLP) field. It uncovers the secrets to enhancing language understanding, and presents practical solutions to different NLP tasks, as text augmentation, paraphrase generation, and restoring spaces and punctuation in multiple languages. It unlocks the potential of hierarchical multi-task learning for cross-lingual phoneme recognition, and allows readers to explore more real-world applications such as error correction, aggregating industrial security findings as well as predicting music emotion values from social media conversations. "Practical Solutions for Diverse Real-World NLP Applications" is the suitable guidebook for researchers, students, and practitioners as it paves the way for them by delivering invaluable insights and knowledge.
Author: Dirk Beyer
Publisher: Springer Nature
ISBN: 3031572599
Category :
Languages : en
Pages : 346
Get Book
Book Description
Author: Noah Gift
Publisher: Addison-Wesley Professional
ISBN: 0134863917
Category : Computers
Languages : en
Pages : 720
Get Book
Book Description
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Author: Eckart Voigts
Publisher: transcript Verlag
ISBN: 3839469228
Category : Social Science
Languages : en
Pages : 293
Get Book
Book Description
As algorithmic data processing increasingly pervades everyday life, it is also making its way into the worlds of art, literature and music. In doing so, it shifts notions of creativity and evokes non-anthropocentric perspectives on artistic practice. This volume brings together contributions from the fields of cultural studies, literary studies, musicology and sound studies as well as media studies, sociology of technology, and beyond, presenting a truly interdisciplinary, state-of-the-art picture of the transformation of creative practice brought about by various forms of AI.
Author: Paul Singh
Publisher: Packt Publishing Ltd
ISBN: 1835080162
Category : Computers
Languages : en
Pages : 301
Get Book
Book Description
Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI Key Features Gain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloud Understand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AI Peek into the future to explore emerging trends like multimodal AI and autonomous agents Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms. This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements. By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.What you will learn Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together Understand how we started applying NLP to concepts like transformers Grasp the process of fine-tuning and developing apps based on RAG 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 Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI Who this book is for This artificial intelligence book is for aspiring cloud architects, data analysts, cloud developers, data scientists, AI researchers, technical business leaders, and technology evangelists looking to understanding the interplay between GenAI and cloud computing. Some chapters provide a broad overview of GenAI, which are suitable for readers with basic to no prior AI experience, aspiring to harness AI's potential. Other chapters delve into technical concepts that require intermediate data and AI skills. A basic understanding of a cloud ecosystem is required to get the most out of this book.
