Large Language Model Based Solutions

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Large Language Model-Based Solutions

Author : Shreyas Subramanian
Publisher : John Wiley & Sons
ISBN 13 : 1394240732
Total Pages : 322 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Large Language Model-Based Solutions by : Shreyas Subramanian

Download or read book Large Language Model-Based Solutions written by Shreyas Subramanian and published by John Wiley & Sons. This book was released on 2024-04-02 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Demystifying Large Language Models

Author : James Chen
Publisher : James Chen
ISBN 13 : 1738908461
Total Pages : 300 pages
Book Rating : 4.7/5 (389 download)

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Book Synopsis Demystifying Large Language Models by : James Chen

Download or read book Demystifying Large Language Models written by James Chen and published by James Chen. This book was released on 2024-04-25 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide aiming to demystify the world of transformers -- the architecture that powers Large Language Models (LLMs) like GPT and BERT. From PyTorch basics and mathematical foundations to implementing a Transformer from scratch, you'll gain a deep understanding of the inner workings of these models. That's just the beginning. Get ready to dive into the realm of pre-training your own Transformer from scratch, unlocking the power of transfer learning to fine-tune LLMs for your specific use cases, exploring advanced techniques like PEFT (Prompting for Efficient Fine-Tuning) and LoRA (Low-Rank Adaptation) for fine-tuning, as well as RLHF (Reinforcement Learning with Human Feedback) for detoxifying LLMs to make them aligned with human values and ethical norms. Step into the deployment of LLMs, delivering these state-of-the-art language models into the real-world, whether integrating them into cloud platforms or optimizing them for edge devices, this section ensures you're equipped with the know-how to bring your AI solutions to life. Whether you're a seasoned AI practitioner, a data scientist, or a curious developer eager to advance your knowledge on the powerful LLMs, this book is your ultimate guide to mastering these cutting-edge models. By translating convoluted concepts into understandable explanations and offering a practical hands-on approach, this treasure trove of knowledge is invaluable to both aspiring beginners and seasoned professionals. Table of Contents 1. INTRODUCTION 1.1 What is AI, ML, DL, Generative AI and Large Language Model 1.2 Lifecycle of Large Language Models 1.3 Whom This Book Is For 1.4 How This Book Is Organized 1.5 Source Code and Resources 2. PYTORCH BASICS AND MATH FUNDAMENTALS 2.1 Tensor and Vector 2.2 Tensor and Matrix 2.3 Dot Product 2.4 Softmax 2.5 Cross Entropy 2.6 GPU Support 2.7 Linear Transformation 2.8 Embedding 2.9 Neural Network 2.10 Bigram and N-gram Models 2.11 Greedy, Random Sampling and Beam 2.12 Rank of Matrices 2.13 Singular Value Decomposition (SVD) 2.14 Conclusion 3. TRANSFORMER 3.1 Dataset and Tokenization 3.2 Embedding 3.3 Positional Encoding 3.4 Layer Normalization 3.5 Feed Forward 3.6 Scaled Dot-Product Attention 3.7 Mask 3.8 Multi-Head Attention 3.9 Encoder Layer and Encoder 3.10 Decoder Layer and Decoder 3.11 Transformer 3.12 Training 3.13 Inference 3.14 Conclusion 4. PRE-TRAINING 4.1 Machine Translation 4.2 Dataset and Tokenization 4.3 Load Data in Batch 4.4 Pre-Training nn.Transformer Model 4.5 Inference 4.6 Popular Large Language Models 4.7 Computational Resources 4.8 Prompt Engineering and In-context Learning (ICL) 4.9 Prompt Engineering on FLAN-T5 4.10 Pipelines 4.11 Conclusion 5. FINE-TUNING 5.1 Fine-Tuning 5.2 Parameter Efficient Fine-tuning (PEFT) 5.3 Low-Rank Adaptation (LoRA) 5.4 Adapter 5.5 Prompt Tuning 5.6 Evaluation 5.7 Reinforcement Learning 5.8 Reinforcement Learning Human Feedback (RLHF) 5.9 Implementation of RLHF 5.10 Conclusion 6. DEPLOYMENT OF LLMS 6.1 Challenges and Considerations 6.2 Pre-Deployment Optimization 6.3 Security and Privacy 6.4 Deployment Architectures 6.5 Scalability and Load Balancing 6.6 Compliance and Ethics Review 6.7 Model Versioning and Updates 6.8 LLM-Powered Applications 6.9 Vector Database 6.10 LangChain 6.11 Chatbot, Example of LLM-Powered Application 6.12 WebUI, Example of LLM-Power Application 6.13 Future Trends and Challenges 6.14 Conclusion REFERENCES ABOUT THE AUTHOR

Artificial Intelligence Applications and Innovations

Author : Ilias Maglogiannis
Publisher : Springer Nature
ISBN 13 : 3031341112
Total Pages : 606 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Artificial Intelligence Applications and Innovations by : Ilias Maglogiannis

Download or read book Artificial Intelligence Applications and Innovations written by Ilias Maglogiannis and published by Springer Nature. This book was released on 2023-05-31 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Web and Big Data. APWeb-WAIM 2023 International Workshops

Author : Xiangyu Song
Publisher : Springer Nature
ISBN 13 : 9819729912
Total Pages : 95 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Web and Big Data. APWeb-WAIM 2023 International Workshops by : Xiangyu Song

Download or read book Web and Big Data. APWeb-WAIM 2023 International Workshops written by Xiangyu Song and published by Springer Nature. This book was released on with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence Ethics and International Law

Author : Abhivardhan
Publisher : BPB Publications
ISBN 13 : 9355516223
Total Pages : 178 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Artificial Intelligence Ethics and International Law by : Abhivardhan

Download or read book Artificial Intelligence Ethics and International Law written by Abhivardhan and published by BPB Publications. This book was released on 2023-12-01 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Practical Solutions for Diverse Real-World NLP Applications

Author : Mourad Abbas
Publisher : Springer Nature
ISBN 13 : 3031442601
Total Pages : 145 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Practical Solutions for Diverse Real-World NLP Applications by : Mourad Abbas

Download or read book Practical Solutions for Diverse Real-World NLP Applications written by Mourad Abbas and published by Springer Nature. This book was released on 2024-02-10 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Fundamental Approaches to Software Engineering

Author : Dirk Beyer
Publisher : Springer Nature
ISBN 13 : 3031572599
Total Pages : 346 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Fundamental Approaches to Software Engineering by : Dirk Beyer

Download or read book Fundamental Approaches to Software Engineering written by Dirk Beyer and published by Springer Nature. This book was released on with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Program Synthesis

Author : Sumit Gulwani
Publisher :
ISBN 13 : 9781680832921
Total Pages : 138 pages
Book Rating : 4.8/5 (329 download)

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Book Synopsis Program Synthesis by : Sumit Gulwani

Download or read book Program Synthesis written by Sumit Gulwani and published by . This book was released on 2017-07-11 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Program synthesis is the task of automatically finding a program in the underlying programming language that satisfies the user intent expressed in the form of some specification. Since the inception of artificial intelligence in the 1950s, this problem has been considered the holy grail of Computer Science. Despite inherent challenges in the problem such as ambiguity of user intent and a typically enormous search space of programs, the field of program synthesis has developed many different techniques that enable program synthesis in different real-life application domains. It is now used successfully in software engineering, biological discovery, compute-raided education, end-user programming, and data cleaning. In the last decade, several applications of synthesis in the field of programming by examples have been deployed in mass-market industrial products. This monograph is a general overview of the state-of-the-art approaches to program synthesis, its applications, and subfields. It discusses the general principles common to all modern synthesis approaches such as syntactic bias, oracle-guided inductive search, and optimization techniques. We then present a literature review covering the four most common state-of-the-art techniques in program synthesis: enumerative search, constraint solving, stochastic search, and deduction-based programming by examples. It concludes with a brief list of future horizons for the field.

Artificial Intelligence - Intelligent Art?

Author : Eckart Voigts
Publisher : transcript Verlag
ISBN 13 : 3839469228
Total Pages : 293 pages
Book Rating : 4.8/5 (394 download)

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Book Synopsis Artificial Intelligence - Intelligent Art? by : Eckart Voigts

Download or read book Artificial Intelligence - Intelligent Art? written by Eckart Voigts and published by transcript Verlag. This book was released on 2024-05-31 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mastering Large Language Models

Author : Sanket Subhash Khandare
Publisher : BPB Publications
ISBN 13 : 9355519656
Total Pages : 465 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Mastering Large Language Models by : Sanket Subhash Khandare

Download or read book Mastering Large Language Models written by Sanket Subhash Khandare and published by BPB Publications. This book was released on 2024-03-12 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Generative AI for Cloud Solutions

Author : Paul Singh
Publisher : Packt Publishing Ltd
ISBN 13 : 1835080162
Total Pages : 301 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Generative AI for Cloud Solutions by : Paul Singh

Download or read book Generative AI for Cloud Solutions written by Paul Singh and published by Packt Publishing Ltd. This book was released on 2024-04-22 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mastering Large Language Models with Python

Author : Raj Arun R
Publisher : Orange Education Pvt Ltd
ISBN 13 : 8197081824
Total Pages : 547 pages
Book Rating : 4.1/5 (97 download)

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Book Synopsis Mastering Large Language Models with Python by : Raj Arun R

Download or read book Mastering Large Language Models with Python written by Raj Arun R and published by Orange Education Pvt Ltd. This book was released on 2024-04-12 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 real-world 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. ● Prioritize the ethical and responsible use of LLMs, with an emphasis on building models that adhere to principles of fairness, transparency, and accountability, fostering trust in AI technologies. 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 AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source 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 well-rounded understanding of LLM implementation. Through real-world 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 AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. WHAT WILL YOU LEARN ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source 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. ● Master prompt engineering techniques to fine-tune LLM outputs, enhancing quality and relevance for diverse use cases. ● Navigate the complex landscape of ethical AI development, prioritizing responsible practices to drive impactful technology adoption and advancement. 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 AI-driven projects, this book is tailored to your needs. TABLE OF CONTENTS 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index

Advancing Software Engineering Through AI, Federated Learning, and Large Language Models

Author : Sharma, Avinash Kumar
Publisher : IGI Global
ISBN 13 :
Total Pages : 375 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Advancing Software Engineering Through AI, Federated Learning, and Large Language Models by : Sharma, Avinash Kumar

Download or read book Advancing Software Engineering Through AI, Federated Learning, and Large Language Models written by Sharma, Avinash Kumar and published by IGI Global. This book was released on 2024-05-02 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.

Enterprise GENERATIVE AI Well-Architected Framework & Patterns

Author : Suvoraj Biswas
Publisher : Packt Publishing Ltd
ISBN 13 : 1836202903
Total Pages : 114 pages
Book Rating : 4.8/5 (362 download)

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Book Synopsis Enterprise GENERATIVE AI Well-Architected Framework & Patterns by : Suvoraj Biswas

Download or read book Enterprise GENERATIVE AI Well-Architected Framework & Patterns written by Suvoraj Biswas and published by Packt Publishing Ltd. This book was released on 2024-04-04 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elevate your AI projects with our course on Enterprise Generative AI using AWS's Well-Architected Framework, paving the way for innovation and efficiency Key Features Learn to secure AI environments Achieve excellence in AI architecture Implement AI with AWS solutions Book DescriptionThe course begins with an insightful introduction to the burgeoning field of Generative AI, laying down a robust framework for understanding its applications within the AWS ecosystem. The course focuses on meticulously detailing the five pillars of the AWS Well-Architected Framework—Operational Excellence, Security, Compliance, Reliability, and Cost Optimization. Each module is crafted to provide you with a comprehensive understanding of these essential areas, integrating Generative AI technologies. You'll learn how to navigate the complexities of securing AI systems, ensuring they comply with legal and regulatory standards, and designing them for unparalleled reliability. Practical sessions on cost optimization strategies for AI projects will empower you to deliver value without compromising on performance or scalability. Furthermore, the course delves into System Architecture Excellence, emphasizing the importance of robust design principles in creating effective Generative AI solutions. The course wraps up by offering a forward-looking perspective on the Common Architectural Pattern for FM/LLM Integration & Adoption within the AWS framework. You'll gain hands-on experience with AWS solutions specifically tailored for Generative AI applications, including Lambda, API Gateway, and DynamoDB, among others.What you will learn Apply Operational Excellence in AI Secure Generative AI implementations Navigate compliance in AI solutions Ensure reliability in AI systems Optimize costs for AI projects Integrate FM/LLM with AWS solutions Who this book is for This course is designed for IT professionals, solutions architects, and DevOps engineers looking to specialize in Generative AI. A foundational understanding of AWS and cloud computing is beneficial.

22nd European Conference on e-Learning

Author : Shawren Singh
Publisher : Academic Conferences and publishing limited
ISBN 13 : 191458791X
Total Pages : 445 pages
Book Rating : 4.9/5 (145 download)

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Book Synopsis 22nd European Conference on e-Learning by : Shawren Singh

Download or read book 22nd European Conference on e-Learning written by Shawren Singh and published by Academic Conferences and publishing limited. This book was released on 2023-10-26 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings represent the work of contributors to the 22nd European Conference on e-Learning (ECEL 2023), hosted by University of South Africa, Pretoria, South Africa on 26-27 October 2023. The Conference Co-Chairs Associate Professor Sarah Jane Johnston and Associate Professor Shawren Singh both from University of South Africa, Pretoria, South Africa. ECEL is now a well-established event on the academic research calendar and now in its 22nd year the key aim remains the opportunity for participants to share ideas and meet the people who hold them. The scope of papers will ensure an interesting two days. The subjects covered illustrate the wide range of topics that fall into this important and ever-growing area of research. It is especially relevant that the conference is being hosted by UNISA this year as the university celebrates its 150th anniversary. UNISA has been a pioneer in first distance and now e-Learning. The conference will also host the final round of the 9th e-Learning Excellence Awards where innovate case histories will be presented. The opening keynote presentation is given by Professor Thenjiwe Meyiwa, Vice Principal for the Research, Postgraduate Studies, Innovation and Commercialisation at University of South Africa who will speak on, “The Role of African Feminisms in Shaping a Sustainable Future of Being and Learning”. An afternoon keynote on Thursday will be made by Dr Zolile Martin Mguda, University of South Africa on the topic of “ChatGPT: The first year”. The second day of the conference will open with an address by Dr Isabel Tarling, MD, Limina, South Africa with the title “Developing Digital Standards for Learning and Teaching in South Africa’s Schools”. With an initial submission of 100 abstracts, after the double blind, peer review process there are 45 Academic research papers, 3 PhD research papers and 1 Masters Research paper published in these Conference Proceedings. These papers represent research from Belgium, Canada, Chile, Czech Republic, France, Germany, Ghana, Greece, Hong Kong, Ireland, Japan, Malaysia, Mozambique, Norway, Oman, Perú, Poland, Portugal, Romania, Singapore, South Africa, Sri Lanka, Sweden, Switzerland, Turkey and the United Kingdom.

Mastering Transformers

Author : Savaş Yıldırım
Publisher : Packt Publishing Ltd
ISBN 13 : 1837631506
Total Pages : 462 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Mastering Transformers by : Savaş Yıldırım

Download or read book Mastering Transformers written by Savaş Yıldırım and published by Packt Publishing Ltd. This book was released on 2024-06-03 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore transformer-based language models from BERT to GPT, delving into NLP and computer vision tasks, while tackling challenges effectively Key Features Understand the complexity of deep learning architecture and transformers architecture Create solutions to industrial natural language processing (NLP) and computer vision (CV) problems Explore challenges in the preparation process, such as problem and language-specific dataset transformation Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTransformer-based language models such as BERT, T5, GPT, DALL-E, and ChatGPT have dominated NLP studies and become a new paradigm. Thanks to their accurate and fast fine-tuning capabilities, transformer-based language models have been able to outperform traditional machine learning-based approaches for many challenging natural language understanding (NLU) problems. Aside from NLP, a fast-growing area in multimodal learning and generative AI has recently been established, showing promising results. Mastering Transformers will help you understand and implement multimodal solutions, including text-to-image. Computer vision solutions that are based on transformers are also explained in the book. You’ll get started by understanding various transformer models before learning how to train different autoregressive language models such as GPT and XLNet. The book will also get you up to speed with boosting model performance, as well as tracking model training using the TensorBoard toolkit. In the later chapters, you’ll focus on using vision transformers to solve computer vision problems. Finally, you’ll discover how to harness the power of transformers to model time series data and for predicting. By the end of this transformers book, you’ll have an understanding of transformer models and how to use them to solve challenges in NLP and CV.What you will learn Focus on solving simple-to-complex NLP problems with Python Discover how to solve classification/regression problems with traditional NLP approaches Train a language model and explore how to fine-tune models to the downstream tasks Understand how to use transformers for generative AI and computer vision tasks Build transformer-based NLP apps with the Python transformers library Focus on language generation such as machine translation and conversational AI in any language Speed up transformer model inference to reduce latency Who this book is for This book is for deep learning researchers, hands-on practitioners, and ML/NLP researchers. Educators, as well as students who have a good command of programming subjects, knowledge in the field of machine learning and artificial intelligence, and who want to develop apps in the field of NLP as well as multimodal tasks will also benefit from this book’s hands-on approach. Knowledge of Python (or any programming language) and machine learning literature, as well as a basic understanding of computer science, are required.

Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series

Author : Igor V. Tetko
Publisher : Springer Nature
ISBN 13 : 3030304906
Total Pages : 761 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series by : Igor V. Tetko

Download or read book Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series written by Igor V. Tetko and published by Springer Nature. This book was released on 2019-09-09 with total page 761 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.