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Scala for Data Science. Leverage the power of Scala with different tools to build scalable, robust data science applications Pascal Bugnion

(ebook) (audiobook) (audiobook) Książka w języku 1
Scala for Data Science. Leverage the power of Scala with different tools to build scalable, robust data science applications Pascal Bugnion - okladka książki

Scala for Data Science. Leverage the power of Scala with different tools to build scalable, robust data science applications Pascal Bugnion - okladka książki

Scala for Data Science. Leverage the power of Scala with different tools to build scalable, robust data science applications Pascal Bugnion - audiobook MP3

Scala for Data Science. Leverage the power of Scala with different tools to build scalable, robust data science applications Pascal Bugnion - audiobook CD

Autor:
Pascal Bugnion
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
416
Dostępne formaty:
     PDF
     ePub
     Mobi
Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines.
This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala.
Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks.
This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.

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O autorze książki

Pascal Bugnion is a data engineer at the ASI, a consultancy offering bespoke data science services. Previously, he was the head of data engineering at SCL Elections. He holds a PhD in computational physics from Cambridge University. Besides Scala, Pascal is a keen Python developer. He has contributed to NumPy, matplotlib and IPython. He also maintains scikit-monaco, an open source library for Monte Carlo integration. He currently lives in London, UK.

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