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Bemærk: Kan ikke leveres før jul.
With the rapid emergence and adoption of new computational design technologies in the field of design, it is important to understand how... Læs mere
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Cut the Gordian Knot of the Social Media Data chaos with the power of Graph Databases. Learn how to combine and migrate data from multiple sources to Neo4j.
Bemærk: Kan ikke leveres før jul.
This book examines the full potential of Digital Twins as a means of creating more sustainable urban habitats. For... Læs mere
Bemærk: Kan ikke leveres før jul.
This book examines the full potential of Digital Twins as a means of creating more sustainable urban habitats. For... Læs mere
Bemærk: Kan ikke leveres før jul.
In this book, Jeremy Stanley and Paige Schwartz from Anomalo explain how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on every category of issue, and resolve problems immediately.
Bemærk: Kan ikke leveres før jul.
Bemærk: Kan ikke leveres før jul.
One of the most popular database systems, Microsoft SQL Server 2019 Express, is presented and implemented in the book with over 40... Læs mere
Bemærk: Kan ikke leveres før jul.
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various... Læs mere
Bemærk: Kan ikke leveres før jul.
With this practical guide, authors Mickael Maison and Kate Stanley show data engineers, site reliability engineers, and application developers how to build data pipelines between Kafka clusters and a variety of data sources and sinks.
Bemærk: Kan ikke leveres før jul.
The concept of deep machine learning is easier to understand by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the cycle-to-cycle variations.
Bemærk: Kan ikke leveres før jul.
With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn.
Bemærk: Kan ikke leveres før jul.