Scala for Data Science : Leverage the Power of Scala with Different Tools to Build Scalable, Robust Data Science Applications
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| Title: | Scala for Data Science : Leverage the Power of Scala with Different Tools to Build Scalable, Robust Data Science Applications |
|---|---|
| Description: | Leverage the power of Scala with different tools to build scalable, robust data science applicationsKey Features[•] A complete guide for scalable data science solutions, from data ingestion to data visualization[•] Deploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizations[•] Build functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples providedBook DescriptionScala 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.What you will learn[•] Transform and filter tabular data to extract features for machine learning[•] Implement your own algorithms or take advantage of MLLib's extensive suite of models to build distributed machine learning pipelines[•] Read, transform, and write data to both SQL and NoSQL databases in a functional manner[•] Write robust routines to query web APIs[•] Read data from web APIs such as the GitHub or Twitter API[•] Use Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirements[•] Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations[•] Deploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveWho this book is forIf you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions. |
| Authors: | Pascal Bugnion |
| Resource Type: | eBook. |
| Subjects: | Scala (Computer program language), Data mining |
| Categories: | COMPUTERS / Programming / Object Oriented, COMPUTERS / Programming / Open Source |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf – Type: ebook-epub Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Scala for Data Science : Leverage the Power of Scala with Different Tools to Build Scalable, Robust Data Science Applications – Name: Abstract Label: Description Group: Ab Data: Leverage the power of Scala with different tools to build scalable, robust data science applicationsKey Features[•] A complete guide for scalable data science solutions, from data ingestion to data visualization[•] Deploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizations[•] Build functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples providedBook DescriptionScala 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.What you will learn[•] Transform and filter tabular data to extract features for machine learning[•] Implement your own algorithms or take advantage of MLLib's extensive suite of models to build distributed machine learning pipelines[•] Read, transform, and write data to both SQL and NoSQL databases in a functional manner[•] Write robust routines to query web APIs[•] Read data from web APIs such as the GitHub or Twitter API[•] Use Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirements[•] Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations[•] Deploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveWho this book is forIf you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Pascal+Bugnion%22">Pascal Bugnion</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Scala+%28Computer+program+language%29%22">Scala (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Programming+%2F+Object+Oriented%22">COMPUTERS / Programming / Object Oriented</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Programming+%2F+Open+Source%22">COMPUTERS / Programming / Open Source</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 005.133 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Scala (Computer program language) Type: general – SubjectFull: Data mining Type: general Titles: – TitleFull: Scala for Data Science : Leverage the Power of Scala with Different Tools to Build Scalable, Robust Data Science Applications Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Pascal Bugnion – PersonEntity: Name: NameFull: Pascal Bugnion IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2016 – D: 29 M: 07 Type: profile Y: 2016 Identifiers: – Type: isbn-print Value: 9781785281372 – Type: isbn-electronic Value: 9781785289385 Titles: – TitleFull: Scala for Data Science : Leverage the Power of Scala with Different Tools to Build Scalable, Robust Data Science Applications Type: main |
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