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Database Design and Modeling with Google Cloud

2023-12-29 Computers
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Release : 2023-12-29
Genre : Computers
Kind : eBook
Book Rating : 865/5 ( reviews)

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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. This book was released on 2023-12-29. 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.

The Developer's Playbook for Large Language Model Security

2024-09-03 Computers
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Release : 2024-09-03
Genre : Computers
Kind : eBook
Book Rating : 161/5 ( reviews)

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Book Synopsis The Developer's Playbook for Large Language Model Security by : Steve Wilson

Download or read book The Developer's Playbook for Large Language Model Security written by Steve Wilson. This book was released on 2024-09-03. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam, focuses exclusively on LLMs, eschewing generalized AI security to delve into the unique characteristics and vulnerabilities inherent in these models. Complete with collective wisdom gained from the creation of the OWASP Top 10 for LLMs list—a feat accomplished by more than 400 industry experts—this guide delivers real-world guidance and practical strategies to help developers and security teams grapple with the realities of LLM applications. Whether you're architecting a new application or adding AI features to an existing one, this book is your go-to resource for mastering the security landscape of the next frontier in AI. You'll learn: Why LLMs present unique security challenges How to navigate the many risk conditions associated with using LLM technology The threat landscape pertaining to LLMs and the critical trust boundaries that must be maintained How to identify the top risks and vulnerabilities associated with LLMs Methods for deploying defenses to protect against attacks on top vulnerabilities Ways to actively manage critical trust boundaries on your systems to ensure secure execution and risk minimization

Machine Learning Design Patterns

2020-10-15 Computers
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Release : 2020-10-15
Genre : Computers
Kind : eBook
Book Rating : 759/5 ( reviews)

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Book Synopsis Machine Learning Design Patterns by : Valliappa Lakshmanan

Download or read book Machine Learning Design Patterns written by Valliappa Lakshmanan. This book was released on 2020-10-15. Available in PDF, EPUB and Kindle. Book excerpt: The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly

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Book Rating : 17X/5 ( reviews)

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LLM Design

2024-05-31 Computers
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Release : 2024-05-31
Genre : Computers
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Book Synopsis LLM Design by : Anand Vemula

Download or read book LLM Design written by Anand Vemula. This book was released on 2024-05-31. Available in PDF, EPUB and Kindle. Book excerpt: "LLM Design: Theory, Architecture, and Applications" is a comprehensive guide that delves into the intricate world of Large Language Models (LLMs), exploring their theoretical foundations, architectural components, and diverse applications. From understanding the fundamental concepts behind language models to implementing them in real-world scenarios, this book serves as an essential resource for researchers, developers, and enthusiasts in the field of artificial intelligence and natural language processing. The book begins by elucidating the theoretical underpinnings of LLMs, discussing key concepts such as language modeling, neural network basics, and the theoretical foundations that drive their development. It then delves into the architectural aspects, covering transformer-based models, variants of transformer architectures, and techniques for handling multilingual data. Readers will gain insights into the training process, including data collection, preprocessing, tokenization, and various training techniques like supervised and unsupervised learning, transfer learning, and fine-tuning. Furthermore, "LLM Design" explores scalability aspects, discussing scaling laws, model parallelism, and data parallelism, essential for training and deploying large-scale language models efficiently. The book also addresses critical topics related to safety, ethics, and model interpretability, emphasizing the importance of fairness, bias mitigation, and transparency in LLM deployment. In the applications and deployment section, readers are introduced to a myriad of NLP applications, including text generation, translation, summarization, and question answering. The deployment strategies discussed cover model serving, API design, and real-time inference, essential for integrating LLMs into diverse applications. Additionally, the book offers insights into maintenance and updates, addressing model monitoring, continuous improvement, and handling model drift to ensure long-term model effectiveness. With its comprehensive coverage of LLM design principles, architectures, and practical applications, "LLM Design: Theory, Architecture, and Applications" is an indispensable guide for anyone seeking to understand and harness the power of large language models in today's AI-driven world.

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