Mastering Java for data science: building data science applications in Java
Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2017
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781782174271/?ar |
| Zusammenfassung: | Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrie... |
| Beschreibung: | Online resource; title from title page (viewed May 15, 2017) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 1785887394 9781785887390 9781782174271 |
Internformat
MARC
| LEADER | 00000cam a22000002 4500 | ||
|---|---|---|---|
| 001 | ZDB-30-ORH-047680024 | ||
| 003 | DE-627-1 | ||
| 005 | 20240228120258.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 191023s2017 xx |||||o 00| ||eng c | ||
| 020 | |a 1785887394 |9 1-78588-739-4 | ||
| 020 | |a 9781785887390 |c electronic bk. |9 978-1-78588-739-0 | ||
| 020 | |a 9781782174271 |9 978-1-78217-427-1 | ||
| 035 | |a (DE-627-1)047680024 | ||
| 035 | |a (DE-599)KEP047680024 | ||
| 035 | |a (ORHE)9781782174271 | ||
| 035 | |a (DE-627-1)047680024 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 082 | 0 | |a 005.133 |2 23 | |
| 100 | 1 | |a Grigorev, Alexey |e VerfasserIn |4 aut | |
| 245 | 1 | 0 | |a Mastering Java for data science |b building data science applications in Java |c Alexey Grigorev |
| 264 | 1 | |a Birmingham, UK |b Packt Publishing |c 2017 | |
| 300 | |a 1 Online-Ressource (1 volume) |b illustrations | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Online resource; title from title page (viewed May 15, 2017) | ||
| 520 | |a Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrie... | ||
| 650 | 0 | |a Java (Computer program language) | |
| 650 | 0 | |a Data mining | |
| 650 | 2 | |a Data Mining | |
| 650 | 4 | |a Java (Langage de programmation) | |
| 650 | 4 | |a Exploration de données (Informatique) | |
| 650 | 4 | |a COMPUTERS ; Data Processing | |
| 650 | 4 | |a COMPUTERS ; Databases ; Data Mining | |
| 650 | 4 | |a COMPUTERS ; Intelligence (AI) & Semantics | |
| 650 | 4 | |a Data mining | |
| 650 | 4 | |a Java (Computer program language) | |
| 966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781782174271/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
| 912 | |a ZDB-30-ORH | ||
| 912 | |a ZDB-30-ORH | ||
| 951 | |a BO | ||
| 912 | |a ZDB-30-ORH | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-30-ORH-047680024 |
|---|---|
| _version_ | 1821494864173334528 |
| adam_text | |
| any_adam_object | |
| author | Grigorev, Alexey |
| author_facet | Grigorev, Alexey |
| author_role | aut |
| author_sort | Grigorev, Alexey |
| author_variant | a g ag |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-30-ORH |
| ctrlnum | (DE-627-1)047680024 (DE-599)KEP047680024 (ORHE)9781782174271 |
| dewey-full | 005.133 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.133 |
| dewey-search | 005.133 |
| dewey-sort | 15.133 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04187cam a22004812 4500</leader><controlfield tag="001">ZDB-30-ORH-047680024</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240228120258.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">191023s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1785887394</subfield><subfield code="9">1-78588-739-4</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781785887390</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">978-1-78588-739-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781782174271</subfield><subfield code="9">978-1-78217-427-1</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047680024</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP047680024</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781782174271</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047680024</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">005.133</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Grigorev, Alexey</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mastering Java for data science</subfield><subfield code="b">building data science applications in Java</subfield><subfield code="c">Alexey Grigorev</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK</subfield><subfield code="b">Packt Publishing</subfield><subfield code="c">2017</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (1 volume)</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Online resource; title from title page (viewed May 15, 2017)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrie...</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Java (Computer program language)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Data Mining</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Java (Langage de programmation)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Exploration de données (Informatique)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">COMPUTERS ; Data Processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">COMPUTERS ; Databases ; Data Mining</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">COMPUTERS ; Intelligence (AI) & Semantics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Java (Computer program language)</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781782174271/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-30-ORH-047680024 |
| illustrated | Illustrated |
| indexdate | 2025-01-17T11:21:09Z |
| institution | BVB |
| isbn | 1785887394 9781785887390 9781782174271 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (1 volume) illustrations |
| psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Packt Publishing |
| record_format | marc |
| spelling | Grigorev, Alexey VerfasserIn aut Mastering Java for data science building data science applications in Java Alexey Grigorev Birmingham, UK Packt Publishing 2017 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title page (viewed May 15, 2017) Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrie... Java (Computer program language) Data mining Data Mining Java (Langage de programmation) Exploration de données (Informatique) COMPUTERS ; Data Processing COMPUTERS ; Databases ; Data Mining COMPUTERS ; Intelligence (AI) & Semantics |
| spellingShingle | Grigorev, Alexey Mastering Java for data science building data science applications in Java Java (Computer program language) Data mining Data Mining Java (Langage de programmation) Exploration de données (Informatique) COMPUTERS ; Data Processing COMPUTERS ; Databases ; Data Mining COMPUTERS ; Intelligence (AI) & Semantics |
| title | Mastering Java for data science building data science applications in Java |
| title_auth | Mastering Java for data science building data science applications in Java |
| title_exact_search | Mastering Java for data science building data science applications in Java |
| title_full | Mastering Java for data science building data science applications in Java Alexey Grigorev |
| title_fullStr | Mastering Java for data science building data science applications in Java Alexey Grigorev |
| title_full_unstemmed | Mastering Java for data science building data science applications in Java Alexey Grigorev |
| title_short | Mastering Java for data science |
| title_sort | mastering java for data science building data science applications in java |
| title_sub | building data science applications in Java |
| topic | Java (Computer program language) Data mining Data Mining Java (Langage de programmation) Exploration de données (Informatique) COMPUTERS ; Data Processing COMPUTERS ; Databases ; Data Mining COMPUTERS ; Intelligence (AI) & Semantics |
| topic_facet | Java (Computer program language) Data mining Data Mining Java (Langage de programmation) Exploration de données (Informatique) COMPUTERS ; Data Processing COMPUTERS ; Databases ; Data Mining COMPUTERS ; Intelligence (AI) & Semantics |
| work_keys_str_mv | AT grigorevalexey masteringjavafordatasciencebuildingdatascienceapplicationsinjava |