Vector Databases For Generative Ai Applications

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Vector Databases for Generative AI Applications

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4./5 ( download)

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Book Synopsis Vector Databases for Generative AI Applications by : Anand Vemula

Download or read book Vector Databases for Generative AI Applications written by Anand Vemula and published by Anand Vemula. This book was released on with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Vector Databases for Generative AI Applications" explores the intersection of two cutting-edge fields: vector databases and generative artificial intelligence (AI). The book provides a comprehensive overview of how vector databases, a specialized form of database optimized for vector similarity search, can enhance various generative AI applications. The first part of the book introduces the fundamentals of vector databases, including key concepts such as vector indexing, similarity search algorithms, and performance optimizations. Readers are guided through the architecture and functionality of vector databases, with a focus on how they differ from traditional relational databases and their suitability for handling high-dimensional data. In the second part, the book delves into the application of vector databases in generative AI. It explores how vector databases can be leveraged to store and retrieve large collections of high-dimensional vectors, which are prevalent in generative AI tasks such as natural language processing, computer vision, and recommender systems. Through real-world examples and case studies, the book demonstrates how vector databases can accelerate the training and inference processes of generative AI models by efficiently managing vector representations of data points. Moreover, the book addresses the challenges and considerations involved in integrating vector databases with generative AI frameworks and platforms. It discusses topics such as data preprocessing, indexing strategies, distributed computing, and scalability, providing practical guidance for architects and developers looking to deploy vector databases in their generative AI pipelines. Throughout the book, the authors highlight the synergies between vector databases and generative AI, showcasing how the combination of these technologies can enable breakthroughs in applications such as content generation, personalized recommendations, and data synthesis. By offering both theoretical insights and hands-on implementation techniques, "Vector Databases for Generative AI Applications" serves as a valuable resource for researchers, practitioners, and enthusiasts seeking to harness the power of vector databases to drive innovation in generative AI.

Building AI Applications with Microsoft Semantic Kernel

Author : Lucas A. Meyer
Publisher : Packt Publishing Ltd
ISBN 13 : 1835469590
Total Pages : 252 pages
Book Rating : 4.8/5 (354 download)

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Book Synopsis Building AI Applications with Microsoft Semantic Kernel by : Lucas A. Meyer

Download or read book Building AI Applications with Microsoft Semantic Kernel written by Lucas A. Meyer and published by Packt Publishing Ltd. This book was released on 2024-06-21 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the power of GenAI by effortlessly linking your C# and Python apps with cutting-edge models, orchestrating diverse AI services with finesse, and crafting bespoke applications through immersive, real-world examples Key Features Link your C# and Python applications with the latest AI models from OpenAI Combine and orchestrate different AI services such as text and image generators Create your own AI apps with real-world use case examples that show you how to use basic generative AI, create images, process documents, use a vector database Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the fast-paced world of AI, developers are constantly seeking efficient ways to integrate AI capabilities into their apps. Microsoft Semantic Kernel simplifies this process by using the GenAI features from Microsoft and OpenAI. Written by Lucas A. Meyer, a Principal Research Scientist in Microsoft’s AI for Good Lab, this book helps you get hands on with Semantic Kernel. It begins by introducing you to different generative AI services such as GPT-3.5 and GPT-4, demonstrating their integration with Semantic Kernel. You’ll then learn to craft prompt templates for reuse across various AI services and variables. Next, you’ll learn how to add functionality to Semantic Kernel by creating your own plugins. The second part of the book shows you how to combine multiple plugins to execute complex actions, and how to let Semantic Kernel use its own AI to solve complex problems by calling plugins, including the ones made by you. The book concludes by teaching you how to use vector databases to expand the memory of your AI services and how to help AI remember the context of earlier requests. You’ll also be guided through several real-world examples of applications, such as RAG and custom GPT agents. By the end of this book, you'll have gained the knowledge you need to start using Semantic Kernel to add AI capabilities to your applications.What you will learn Write reusable AI prompts and connect to different AI providers Create new plugins that extend the capabilities of AI services Understand how to combine multiple plugins to execute complex actions Orchestrate multiple AI services to accomplish a task Leverage the powerful planner to automatically create appropriate AI calls Use vector databases as additional memory for your AI tasks Deploy your application to ChatGPT, making it available to hundreds of millions of users Who this book is for This book is for beginner-level to experienced .NET or Python software developers who want to quickly incorporate the latest AI technologies into their applications, without having to learn the details of every new AI service. Product managers with some development experience will find this book helpful while creating proof-of-concept applications. This book requires working knowledge of programming basics.

Applications of Generative AI

Author : Zhihan Lyu
Publisher : Springer Nature
ISBN 13 : 3031462386
Total Pages : 607 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Applications of Generative AI by : Zhihan Lyu

Download or read book Applications of Generative AI written by Zhihan Lyu and published by Springer Nature. This book was released on with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Google Machine Learning and Generative AI for Solutions Architects

Author : Kieran Kavanagh
Publisher : Packt Publishing Ltd
ISBN 13 : 1803247029
Total Pages : 552 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Google Machine Learning and Generative AI for Solutions Architects by : Kieran Kavanagh

Download or read book Google Machine Learning and Generative AI for Solutions Architects written by Kieran Kavanagh and published by Packt Publishing Ltd. This book was released on 2024-06-28 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectively Key Features Understand key concepts, from fundamentals through to complex topics, via a methodical approach Build real-world end-to-end MLOps solutions and generative AI applications on Google Cloud Get your hands on a code repository with over 20 hands-on projects for all stages of the ML model development lifecycle Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionNearly all companies nowadays either already use or are trying to incorporate AI/ML into their businesses. While AI/ML research is undoubtedly complex, the building and running of apps that utilize AI/ML effectively is tougher. This book shows you exactly how to design and run AI/ML workloads successfully using years of experience some of the world’s leading tech companies have to offer. You’ll begin by gaining a clear understanding of essential fundamental AI/ML concepts, before moving on to grasp complex topics with the help of examples and hands-on activities. This will help you eventually explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. As you advance, you’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these challenges. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process. By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.What you will learn Build solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and Spark Source, understand, and prepare data for ML workloads Build, train, and deploy ML models on Google Cloud Create an effective MLOps strategy and implement MLOps workloads on Google Cloud Discover common challenges in typical AI/ML projects and get solutions from experts Explore vector databases and their importance in Generative AI applications Uncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflows Who this book is for This book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material.

Database Design and Modeling with Google Cloud

Author : Abirami Sukumaran
Publisher : Packt Publishing Ltd
ISBN 13 : 1804617865
Total Pages : 234 pages
Book Rating : 4.8/5 (46 download)

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Book Synopsis Database Design and Modeling with Google Cloud by : Abirami Sukumaran

Download or read book Database Design and Modeling with Google Cloud written by Abirami Sukumaran and published by Packt Publishing Ltd. This book was released on 2023-12-29 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needs Key Features Familiarize yourself with business and technical considerations involved in modeling the right database Take your data to applications, analytics, and AI with real-world examples Learn how to code, build, and deploy end-to-end solutions with expert advice Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you’ll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You’ll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.What you will learn Understand different use cases and real-world applications of data in the cloud Work with document and indexed NoSQL databases Get to grips with modeling considerations for analytics, AI, and ML Use real-world examples to learn about ETL services Design structured, semi-structured, and unstructured data for your applications and analytics Improve observability, performance, security, scalability, latency SLAs, SLIs, and SLOs Who this book is for This book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data.

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.

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.

Generative AI on AWS

Author : Chris Fregly
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098159195
Total Pages : 312 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Generative AI on AWS by : Chris Fregly

Download or read book Generative AI on AWS written by Chris Fregly and published by "O'Reilly Media, Inc.". This book was released on 2023-11-13 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock

Generative AI with LangChain

Author : Ben Auffarth
Publisher : Packt Publishing Ltd
ISBN 13 : 1835088368
Total Pages : 361 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Generative AI with LangChain by : Ben Auffarth

Download or read book Generative AI with LangChain written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2023-12-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. Code examples are regularly updated on GitHub to keep you abreast of the latest LangChain developments. Purchase of the print or Kindle book includes a free PDF eBook. Key Features GitHub repository updated regularly to stay abreast of LangChain developments Delve into the realm of LLMs with LangChain and go on an in-depth exploration of their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Bard. It also demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Understand LLMs, their strengths and limitations Grasp generative AI fundamentals and industry trends Create LLM apps with LangChain like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LLMs. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs and are looking to stay ahead of the curve in the LLMs and LangChain arena. Basic knowledge of Python is a prerequisite, while some prior exposure to machine learning will help you follow along more easily.

Generative AI Business Applications

Author : David E. Sweenor
Publisher : TinyTechMedia LLC
ISBN 13 :
Total Pages : 60 pages
Book Rating : 4.9/5 (893 download)

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Book Synopsis Generative AI Business Applications by : David E. Sweenor

Download or read book Generative AI Business Applications written by David E. Sweenor and published by TinyTechMedia LLC. This book was released on 2024-01-31 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the past year, generative AI has broken barriers and transformed how we think about what computers are truly capable of. But, with the marketing hype and generative AI washing of content, it’s increasingly difficult for business leaders and practitioners to go beyond the art of the possible and answer that critical question–how is generative AI actually being used in organizations? With over 70 real-world case studies and applications across 12 different industries and 11 departments, Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies fills a critical knowledge gap for business leaders and practitioners by providing examples of generative AI in action. Diving into the case studies, this TinyTechGuide discusses AI risks, implementation considerations, generative AI operations, AI ethics, and trustworthy AI. The world is transforming before our very eyes. Don’t get left behind—while understanding the powers and perils of generative AI. Full of use cases and real-world applications, this book is designed for business leaders, tech professionals, and IT teams. We provide practical, jargon-free explanations of generative AI's transformative power. Gain a competitive edge in today's marketplace with Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies. Remember, it's not the tech that's tiny, just the book!™

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.

Learn Python Generative AI

Author : Zonunfeli Ralte
Publisher : BPB Publications
ISBN 13 : 9355518978
Total Pages : 421 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Learn Python Generative AI by : Zonunfeli Ralte

Download or read book Learn Python Generative AI written by Zonunfeli Ralte and published by BPB Publications. This book was released on 2024-02-01 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to unleash the power of AI creativity KEY FEATURES ● Understand the core concepts related to generative AI. ● Different types of generative models and their applications. ● Learn how to design generative AI neural networks using Python and TensorFlow. DESCRIPTION This book researches the intricate world of generative Artificial Intelligence, offering readers an extensive understanding of various components and applications in this field. The book begins with an in-depth analysis of generative models, providing a solid foundation and exploring their combination nuances. It then focuses on enhancing TransVAE, a variational autoencoder, and introduces the Swin Transformer in generative AI. The inclusion of cutting edge applications like building an image search using Pinecone and a vector database further enriches its content. The narrative shifts to practical applications, showcasing GenAI's impact in healthcare, retail, and finance, with real-world examples and innovative solutions. In the healthcare sector, it emphasizes AI's transformative role in diagnostics and patient care. In retail and finance, it illustrates how AI revolutionizes customer engagement and decision making. The book concludes by synthesizing key learnings, offering insights into the future of generative AI, and making it a comprehensive guide for diverse industries. Readers will find themselves equipped with a profound understanding of generative AI, its current applications, and its boundless potential for future innovations. WHAT YOU WILL LEARN ● Acquire practical skills in designing and implementing various generative AI models. ● Gain expertise in vector databases and image embeddings, crucial for image search and data retrieval. ● Navigate challenges in healthcare, retail, and finance using sector specific insights. ● Generate images and text with VAEs, GANs, LLMs, and vector databases. ● Focus on both traditional and cutting edge techniques in generative AI. WHO THIS BOOK IS FOR This book is for current and aspiring emerging AI deep learning professionals, architects, students, and anyone who is starting and learning a rewarding career in generative AI. TABLE OF CONTENTS 1. Introducing Generative AI 2. Designing Generative Adversarial Networks 3. Training and Developing Generative Adversarial Networks 4. Architecting Auto Encoder for Generative AI 5. Building and Training Generative Autoencoders 6. Designing Generative Variation Auto Encoder 7. Building Variational Autoencoders for Generative AI 8. Fundamental of Designing New Age Generative Vision Transformer 9. Implementing Generative Vision Transformer 10. Architectural Refactoring for Generative Modeling 11. Major Technical Roadblocks in Generative AI and Way Forward 12. Overview and Application of Generative AI Models 13. Key Learnings

Kubernetes and Cloud Native Associate (KCNA) Study Guide

Author : Jorge Valenzuela Jiménez
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098138910
Total Pages : 266 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Kubernetes and Cloud Native Associate (KCNA) Study Guide by : Jorge Valenzuela Jiménez

Download or read book Kubernetes and Cloud Native Associate (KCNA) Study Guide written by Jorge Valenzuela Jiménez and published by "O'Reilly Media, Inc.". This book was released on 2024-05-29 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to prepare for—and pass—the Kubernetes and Cloud Native Associate (KCNA) certification exam. This practical guide serves as both a study guide and point of entry for practitioners looking to explore and adopt cloud native technologies. Adrián González Sánchez and Jorge Valenzuela Jiménez teach you not only the core technology fundamentals, but also the community and industry that KCNA serves. With the meteoric rise in cloud adoption, cloud native technologies such as Kubernetes have become the de facto industry standard. Other Kubernetes certifications—including KCSA, CKAD, CKA, and CKS—are all geared toward higher-level technical proficiency. The KCNA is the entry door to your cloud native journey, and the certification exam covers the cloud native environment generally as well as fundamental Kubernetes skills and knowledge. This guide helps you learn: How to best and most efficiently prepare for the KCNA exam The latest cloud native developments and their importance The fundamentals of Kubernetes, cloud native development, and related CNCF projects The core elements of Kubernetes applications The crucial elements of modern cloud native development How to differentiate and choose cloud native technologies The market value of passing the KCNA exam Insights and testimonials from key cloud native industry experts

CTO.online

Author : Andre Buren
Publisher : Mijnbestseller.nl
ISBN 13 : 9403725508
Total Pages : 1070 pages
Book Rating : 4.4/5 (37 download)

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Book Synopsis CTO.online by : Andre Buren

Download or read book CTO.online written by Andre Buren and published by Mijnbestseller.nl. This book was released on 2023-12-31 with total page 1070 pages. Available in PDF, EPUB and Kindle. Book excerpt: The role of CTO is evolving fast, thinking strategically about technology and business opportunities. As we navigate this new world, we face the challenge of harnessing the immense potential of new online technologies for our business. You will need to wear multiple hats, including innovator, business leader, and most of all change agent. In these exhilarating yet turbulent times, being a tech leader means having the vision to steer your ship through stormy seas of disruption and guide it towards the tranquil waters of progress. It requires the foresight to anticipate what lies ahead and the adaptability to embrace change. It calls for the audacity to take risks and the humility to learn from mistakes. CTO.online is your comprehensive guide covering all the expertise necessary for modern-day online tech leadership. It provides actionable guidance, advice, practical tips, and perspectives from firsthand experience and industry leaders. The book includes contributions from renowned tech leaders and thinkers, offering diverse perspectives on technology leadership.

AI-Assisted Programming

Author : Tom Taulli
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098164571
Total Pages : 225 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis AI-Assisted Programming by : Tom Taulli

Download or read book AI-Assisted Programming written by Tom Taulli and published by "O'Reilly Media, Inc.". This book was released on 2024-04-10 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs

Developing Kaggle Notebooks

Author : Gabriel Preda
Publisher : Packt Publishing Ltd
ISBN 13 : 1805125710
Total Pages : 371 pages
Book Rating : 4.8/5 (51 download)

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Book Synopsis Developing Kaggle Notebooks by : Gabriel Preda

Download or read book Developing Kaggle Notebooks written by Gabriel Preda and published by Packt Publishing Ltd. This book was released on 2023-12-27 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printed in Color Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact Leverage the power of Generative AI with Kaggle Models Purchase of the print or Kindle book includes a free PDF eBook Key Features Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound Improve the style and readability of your Notebooks, making them more impactful and compelling Book DescriptionDeveloping Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques. For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable. Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.What you will learn Approach a dataset or competition to perform data analysis via a notebook Learn data ingestion and address issues arising with the ingested data Structure your code using reusable components Analyze in depth both small and large datasets of various types Distinguish yourself from the crowd with the content of your analysis Enhance your notebook style with a color scheme and other visual effects Captivate your audience with data and compelling storytelling techniques Who this book is for This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any background Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings Professionals who already use Kaggle for learning and competing

Prompt Engineering for Generative AI

Author : James Phoenix
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098153405
Total Pages : 423 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Prompt Engineering for Generative AI by : James Phoenix

Download or read book Prompt Engineering for Generative AI written by James Phoenix and published by "O'Reilly Media, Inc.". This book was released on 2024-05-16 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture—and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code