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Data Engineering Design Patterns

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Machine Learning Design Patterns

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Author : Valliappa Lakshmanan
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-15

Machine Learning Design Patterns written by Valliappa Lakshmanan and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with Computers categories.

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

Design Patterns

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Author : Erich Gamma
language : en
Publisher: Pearson Deutschland GmbH
Release Date : 1995

Design Patterns written by Erich Gamma and has been published by Pearson Deutschland GmbH this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Business & Economics categories.

Software -- Software Engineering.

Data Engineering Design Patterns

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Author : Bartosz Konieczny
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-09

Data Engineering Design Patterns written by Bartosz Konieczny and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-09 with Computers categories.

Data projects are an intrinsic part of an organization’s technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more. Author Bartosz Konieczny guides you through the process of building reliable end-to-end data engineering projects, from data ingestion to data observability, focusing on data engineering design patterns that solve common business problems in a secure and storage-optimized manner. Each pattern includes a user-facing description of the problem, solutions, and consequences that place the pattern into the context of real-life scenarios. Throughout this journey, you’ll use open source data tools and public cloud services to apply each pattern. You'll learn: Challenges data engineers face and their impact on data systems How these challenges relate to data system components Useful applications of data engineering patterns How to identify and fix issues with your current data components TTechnology-agnostic solutions to new and existing data projects, with open source implementation examples Bartosz Konieczny is a freelance data engineer who's been coding since 2010. He's held various senior hands-on positions that allowed him to work on many data engineering problems in batch and stream processing.

Data Pipelines Pocket Reference

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Author : James Densmore
language : en
Publisher: O'Reilly Media
Release Date : 2021-02-10

Data Pipelines Pocket Reference written by James Densmore and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-10 with Computers categories.

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting

Design Patterns For Cloud Native Applications

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Author : Kasun Indrasiri
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-17

Design Patterns For Cloud Native Applications written by Kasun Indrasiri and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-17 with Computers categories.

With the immense cost savings and scalability the cloud provides, the rationale for building cloud native applications is no longer in question. The real issue is how. With this practical guide, developers will learn about the most commonly used design patterns for building cloud native applications using APIs, data, events, and streams in both greenfield and brownfield development. You'll learn how to incrementally design, develop, and deploy large and effective cloud native applications that you can manage and maintain at scale with minimal cost, time, and effort. Authors Kasun Indrasiri and Sriskandarajah Suhothayan highlight use cases that effectively demonstrate the challenges you might encounter at each step. Learn the fundamentals of cloud native applications Explore key cloud native communication, connectivity, and composition patterns Learn decentralized data management techniques Use event-driven architecture to build distributed and scalable cloud native applications Explore the most commonly used patterns for API management and consumption Examine some of the tools and technologies you'll need for building cloud native systems

Architectural Patterns

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Author : Pethuru Raj Chelliah
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-12-22

Architectural Patterns written by Pethuru Raj Chelliah and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-22 with Computers categories.

Learn the importance of architectural and design patterns in producing and sustaining next-generation IT and business-critical applications with this guide. About This Book Use patterns to tackle communication, integration, application structure, and more Implement modern design patterns such as microservices to build resilient and highly available applications Choose between the MVP, MVC, and MVVM patterns depending on the application being built Who This Book Is For This book will empower and enrich IT architects (such as enterprise architects, software product architects, and solution and system architects), technical consultants, evangelists, and experts. What You Will Learn Understand how several architectural and design patterns work to systematically develop multitier web, mobile, embedded, and cloud applications Learn object-oriented and component-based software engineering principles and patterns Explore the frameworks corresponding to various architectural patterns Implement domain-driven, test-driven, and behavior-driven methodologies Deploy key platforms and tools effectively to enable EA design and solutioning Implement various patterns designed for the cloud paradigm In Detail Enterprise Architecture (EA) is typically an aggregate of the business, application, data, and infrastructure architectures of any forward-looking enterprise. Due to constant changes and rising complexities in the business and technology landscapes, producing sophisticated architectures is on the rise. Architectural patterns are gaining a lot of attention these days. The book is divided in three modules. You'll learn about the patterns associated with object-oriented, component-based, client-server, and cloud architectures. The second module covers Enterprise Application Integration (EAI) patterns and how they are architected using various tools and patterns. You will come across patterns for Service-Oriented Architecture (SOA), Event-Driven Architecture (EDA), Resource-Oriented Architecture (ROA), big data analytics architecture, and Microservices Architecture (MSA). The final module talks about advanced topics such as Docker containers, high performance, and reliable application architectures. The key takeaways include understanding what architectures are, why they're used, and how and where architecture, design, and integration patterns are being leveraged to build better and bigger systems. Style and Approach This book adopts a hands-on approach with real-world examples and use cases.

Data Engineering Design Patterns

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Author : Bartosz Konieczny
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-09

Data Engineering With Apache Spark Delta Lake And Lakehouse

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Author : Manoj Kukreja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-22

Data Engineering With Apache Spark Delta Lake And Lakehouse written by Manoj Kukreja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.

Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key FeaturesBecome well-versed with the core concepts of Apache Spark and Delta Lake for building data platformsLearn how to ingest, process, and analyze data that can be later used for training machine learning modelsUnderstand how to operationalize data models in production using curated dataBook Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. What you will learnDiscover the challenges you may face in the data engineering worldAdd ACID transactions to Apache Spark using Delta LakeUnderstand effective design strategies to build enterprise-grade data lakesExplore architectural and design patterns for building efficient data ingestion pipelinesOrchestrate a data pipeline for preprocessing data using Apache Spark and Delta Lake APIsAutomate deployment and monitoring of data pipelines in productionGet to grips with securing, monitoring, and managing data pipelines models efficientlyWho this book is for This book is for aspiring data engineers and data analysts who are new to the world of data engineering and are looking for a practical guide to building scalable data platforms. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Basic knowledge of Python, Spark, and SQL is expected.

Ontology Engineering With Ontology Design Patterns Foundations And Applications

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Author : P. Hitzler
language : en
Publisher: IOS Press
Release Date : 2016-09-16

Ontology Engineering With Ontology Design Patterns Foundations And Applications written by P. Hitzler and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-16 with Computers categories.

The use of ontologies for data and knowledge organization has become ubiquitous in many data-intensive and knowledge-driven application areas, in science, industry, and the humanities. At the same time, ontology engineering best practices continue to evolve. In particular, modular ontology modeling based on ontology design patterns is establishing itself as an approach for creating versatile and extendable ontologies for data management and integration. This book is the very first comprehensive treatment of Ontology Engineering with Ontology Design Patterns. It contains both advanced and introductory material accessible for readers with only a minimal background in ontology modeling. Some introductory material is written in the style of tutorials, and specific chapters are devoted to examples and to applications. Other chapters convey the state of the art in research regarding ontology design patterns. The editors and the contributing authors include the leading contributors to the development of ontology-design-pattern-driven ontology engineering.

Api Design Patterns

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Author : JJ Geewax
language : en
Publisher: Simon and Schuster
Release Date : 2021-07-20

Api Design Patterns written by JJ Geewax and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-20 with Computers categories.

Modern software systems are composed of many servers, services, and other components that communicate through APIs. As a developer, your job is to make sure these APIs are stable, reliable, and easy to use for other developers. API Design Patterns provides you with a unique catalog of design standards and best practices to ensure your APIs are flexible and user-friendly. Fully illustrated with examples and relevant use-cases, this essential guide covers patterns for API fundamentals and real-world system designs, along with quite a few not-so-common scenarios and edge-cases. about the technology API design patterns are a useful set of best practice specifications and common solutions to API design challenges. Using accepted design patterns creates a shared language amongst developers who create and consume APIs, which is especially critical given the explosion of mission-critical public-facing web APIs. API Patterns are still being developed and discovered. This collection, gathered and tested by Google API expert JJ Geewax, is the first of its kind. about the book API Design Patterns draws on the collected wisdom of the API community, including the internal developer knowledge base at Google, laying out an innovative set of design patterns for developing both internal and public-facing APIs. In this essential guide, Google Software Engineer JJ Geewax provides a unique and authoritative catalog of patterns that promote flexibility and ease-of-use in your APIs. Each pattern in the catalog is fully illustrated with its own example API, use-cases for solving common API design challenges, and scenarios for tricky edge issues using a pattern''s more subtle features. With the best practices laid out in this book, you can ensure your APIs are adaptive in the face of change and easy for your clients to incorporate into their projects. what''s inside A full case-study of building an API and adding features The guiding principles that underpin most API patterns Fundamental patterns for resource layout and naming Advanced patterns for special interactions and data transformations about the reader Aimed at software developers with experience using APIs, who want to start building their own. about the author JJ Geewax is a software engineer at Google, focusing on Google Cloud Platform and API design. He is also the author of Google Cloud Platform in Action.

Data Engineering Design Patterns

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