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Designing Data-Intensive Applications

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Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data warehouses, and data lakes. There are cloud services, on-premises services, and embedded databases. What ... Read more

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Data that parses is not necessarily data that is correct.Data Format Engineering explains how leading zeros, nulls, time zones, monetary precision, API contracts, event versions, privacy controls, and analytical storage change the way systems interpret data.The book covers CSV, JSON, YAML, XML, Avro, Protobuf, Parquet, and ORC, backed by an executable HappyShop example that builds a cross-platform ... Read more

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数据科学原理

Chinese Edition

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Domain-Driven Transformation

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by Carola Lilienthal, Henning Schwentner ...

To prepare legacy software for the future, it's essential to modernize it. Domain-Driven Transformation provides an effective approach for transforming large legacy systems—either by breaking them into microservices or by converting them into maintainable modular monoliths.In this guide, Carola Lilienthal and Henning Schwentner present their method, a comprehensive approach for transforming ... Read more

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Hands-On Machine Learning with C++

Build, train, and deploy end-to-end machine learning and deep learning pipelines

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Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasetsKey FeaturesBecome familiar with data processing, performance measuring, and model selection using various C++ librariesImplement practical machine learning and deep learning techniques to build ... Read more

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Visualizing Streaming Data

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