Materias:

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Materias: “…Streaming technology (Telecommunications)…”
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Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Section 1: Introduction to Data Streaming and Amazon Kinesis -- Chapter 1: What Are Data Streams? …”

“…Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? …”

“…Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. …”

“…Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? …”

Tabla de Contenidos: “…Table of Contents An Introduction to Streaming Data Architectures for Streaming and Real-Time Machine Learning Data Analysis on Streaming Data Online Learning with River Online Anomaly Detection Online Classification Online Regression Reinforcement Learning Drift and Drift Detection Feature Transformation and Scaling Catastrophic Forgetting Conclusion and Best Practices…”

“…4 Hours of Video Instruction Learn value stream mapping key concepts, including the principles of Lean thinking, a high-level overview of the value stream mapping process, and when and how to use this strategic, transformative approach to significantly improve and optimize performance. …”

Materias:

Tabla de Contenidos: “…Intro -- Azure Storage, Streaming, and Batch Analytic -- Copyright -- dedication -- brief contents -- contents -- front matter -- preface -- acknowledgements -- about this book -- Who should read this book -- How this book is organized: a roadmap -- About the code -- Author online -- about the author -- about the cover illustration -- 1 What is data engineering? …”

Tabla de Contenidos: “…Front cover; Contents; List of Tables; List of Figures; List of Algorithms; Foreword; Acknowledgments; Chapter 1: Knowledge Discovery from Data Streams; Chapter 2: Introduction to Data Streams; Chapter 3: Change Detection; Chapter 4: Maintaining Histograms from Data Streams; Chapter 5: Evaluating Streaming Algorithms; Chapter 6: Clustering from Data Streams; Chapter 7: Frequent Pattern Mining; Chapter 8: Decision Trees from Data Streams; Chapter 9: Novelty Detection in Data Streams; Chapter 10: Ensembles of Classiers; Chapter 11: Time Series Data Streams; Chapter 12: Ubiquitous Data Mining…”

“…He examines the concept of 'polyglot persistence' and the proper usage of different styles of databases, caches, and streaming solutions. You'll consider effective patterns for combining these technologies, using Apache Cassandra and Apache Kafka as examples."…”