Building a recommendation engine with Scala: learn to use Scala to build a recommendation engine from scratch and empower your website users
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2016
|
| Schriftenreihe: | Community experience distilled
|
| Schlagworte: | |
| Beschreibung: | Online resource; title from cover page (Safari, viewed January 21, 2016). - Includes index |
| Beschreibung: | 1 online resource illustrations |
| ISBN: | 9781785282980 1785282980 1785282581 9781785282584 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV045351543 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 181210s2016 |||| o||u| ||||||eng d | ||
| 020 | |a 9781785282980 |9 978-1-78528-298-0 | ||
| 020 | |a 1785282980 |9 1-78528-298-0 | ||
| 020 | |a 1785282581 |9 1-78528-258-1 | ||
| 020 | |a 9781785282584 |9 978-1-78528-258-4 | ||
| 024 | 3 | |a 9781785282584 | |
| 035 | |a (ZDB-4-ITC)ocn935744746 | ||
| 035 | |a (OCoLC)935744746 | ||
| 035 | |a (DE-599)BVBBV045351543 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 082 | 0 | |a 005.114 |2 23 | |
| 100 | 1 | |a Ansari, Saleem |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Building a recommendation engine with Scala |b learn to use Scala to build a recommendation engine from scratch and empower your website users |c Saleem Ansari |
| 264 | 1 | |a Birmingham, UK |b Packt Publishing |c 2016 | |
| 300 | |a 1 online resource |b illustrations | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Community experience distilled | |
| 500 | |a Online resource; title from cover page (Safari, viewed January 21, 2016). - Includes index | ||
| 505 | 8 | |a Learn to use Scala to build a recommendation engine from scratch and empower your website usersAbout This Book Learn the basics of a recommendation engine and its application in e-commerce Discover the tools and machine learning methods required to build a recommendation engine Explore different kinds of recommendation engines using Scala libraries such as MLib and SparkWho This Book Is ForThis book is written for those who want to learn the different tools in the Scala ecosystem to build a recommendation engine. No prior knowledge of Scala or recommendation engines is assumed. | |
| 505 | 8 | |a What You Will Learn Discover the tools in the Scala ecosystem Understand the challenges faced in e-commerce systems and learn how you can solve those challenges with a recommendation engine Familiarise yourself with machine learning algorithms provided by the Apache Spark framework Build different versions of recommendation engines from practical code examples Enhance the user experience by learning from user feedback Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendationsIn DetailWith an increase of data in online e-commerce systems, the challenges in assisting users with narrowing down their search have grown dramatically. The various tools available in the Scala ecosystem enable developers to build a processing pipeline to meet those challenges and create a recommendation system to accelerate business growth and leverage brand advocacy for your clients. | |
| 505 | 8 | |a This book provides you with the Scala knowledge you need to build a recommendation engine. You'll be introduced to Scala and other related tools to set the stage for the project and familiarise yourself with the different stages in the data processing pipeline, including at which stages you can leverage the power of Scala and related tools. You'll also discover different machine learning algorithms using MLLib. As the book progresses, you will gain detailed knowledge of what constitutes a collaborative filtering based recommendation and explore different methods to improve users' recommendation. Style and approachA step-by-step guide full of real-world, hands-on examples of Scala recommendation engines. Each example is placed in context with explanation and visuals | |
| 650 | 7 | |a COMPUTERS / Programming Languages / General |2 bisacsh | |
| 650 | 7 | |a Functional programming languages |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Scala (Computer program language) |2 fast | |
| 650 | 4 | |a Scala (Computer program language) |a Functional programming languages |a Machine learning | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |
| 912 | |a ZDB-4-ITC | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-030738197 | ||
Datensatz im Suchindex
| _version_ | 1804179177098706944 |
|---|---|
| any_adam_object | |
| author | Ansari, Saleem |
| author_facet | Ansari, Saleem |
| author_role | aut |
| author_sort | Ansari, Saleem |
| author_variant | s a sa |
| building | Verbundindex |
| bvnumber | BV045351543 |
| collection | ZDB-4-ITC |
| contents | Learn to use Scala to build a recommendation engine from scratch and empower your website usersAbout This Book Learn the basics of a recommendation engine and its application in e-commerce Discover the tools and machine learning methods required to build a recommendation engine Explore different kinds of recommendation engines using Scala libraries such as MLib and SparkWho This Book Is ForThis book is written for those who want to learn the different tools in the Scala ecosystem to build a recommendation engine. No prior knowledge of Scala or recommendation engines is assumed. What You Will Learn Discover the tools in the Scala ecosystem Understand the challenges faced in e-commerce systems and learn how you can solve those challenges with a recommendation engine Familiarise yourself with machine learning algorithms provided by the Apache Spark framework Build different versions of recommendation engines from practical code examples Enhance the user experience by learning from user feedback Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendationsIn DetailWith an increase of data in online e-commerce systems, the challenges in assisting users with narrowing down their search have grown dramatically. The various tools available in the Scala ecosystem enable developers to build a processing pipeline to meet those challenges and create a recommendation system to accelerate business growth and leverage brand advocacy for your clients. This book provides you with the Scala knowledge you need to build a recommendation engine. You'll be introduced to Scala and other related tools to set the stage for the project and familiarise yourself with the different stages in the data processing pipeline, including at which stages you can leverage the power of Scala and related tools. You'll also discover different machine learning algorithms using MLLib. As the book progresses, you will gain detailed knowledge of what constitutes a collaborative filtering based recommendation and explore different methods to improve users' recommendation. Style and approachA step-by-step guide full of real-world, hands-on examples of Scala recommendation engines. Each example is placed in context with explanation and visuals |
| ctrlnum | (ZDB-4-ITC)ocn935744746 (OCoLC)935744746 (DE-599)BVBBV045351543 |
| dewey-full | 005.114 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.114 |
| dewey-search | 005.114 |
| dewey-sort | 15.114 |
| 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>03945nmm a2200457zc 4500</leader><controlfield tag="001">BV045351543</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">181210s2016 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781785282980</subfield><subfield code="9">978-1-78528-298-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1785282980</subfield><subfield code="9">1-78528-298-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1785282581</subfield><subfield code="9">1-78528-258-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781785282584</subfield><subfield code="9">978-1-78528-258-4</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9781785282584</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-4-ITC)ocn935744746</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)935744746</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV045351543</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">005.114</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ansari, Saleem</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Building a recommendation engine with Scala</subfield><subfield code="b">learn to use Scala to build a recommendation engine from scratch and empower your website users</subfield><subfield code="c">Saleem Ansari</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK</subfield><subfield code="b">Packt Publishing</subfield><subfield code="c">2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Community experience distilled</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Online resource; title from cover page (Safari, viewed January 21, 2016). - Includes index</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Learn to use Scala to build a recommendation engine from scratch and empower your website usersAbout This Book Learn the basics of a recommendation engine and its application in e-commerce Discover the tools and machine learning methods required to build a recommendation engine Explore different kinds of recommendation engines using Scala libraries such as MLib and SparkWho This Book Is ForThis book is written for those who want to learn the different tools in the Scala ecosystem to build a recommendation engine. No prior knowledge of Scala or recommendation engines is assumed. </subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">What You Will Learn Discover the tools in the Scala ecosystem Understand the challenges faced in e-commerce systems and learn how you can solve those challenges with a recommendation engine Familiarise yourself with machine learning algorithms provided by the Apache Spark framework Build different versions of recommendation engines from practical code examples Enhance the user experience by learning from user feedback Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendationsIn DetailWith an increase of data in online e-commerce systems, the challenges in assisting users with narrowing down their search have grown dramatically. The various tools available in the Scala ecosystem enable developers to build a processing pipeline to meet those challenges and create a recommendation system to accelerate business growth and leverage brand advocacy for your clients. </subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">This book provides you with the Scala knowledge you need to build a recommendation engine. You'll be introduced to Scala and other related tools to set the stage for the project and familiarise yourself with the different stages in the data processing pipeline, including at which stages you can leverage the power of Scala and related tools. You'll also discover different machine learning algorithms using MLLib. As the book progresses, you will gain detailed knowledge of what constitutes a collaborative filtering based recommendation and explore different methods to improve users' recommendation. Style and approachA step-by-step guide full of real-world, hands-on examples of Scala recommendation engines. Each example is placed in context with explanation and visuals</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">COMPUTERS / Programming Languages / General</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Functional programming languages</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Scala (Computer program language)</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Scala (Computer program language)</subfield><subfield code="a">Functional programming languages</subfield><subfield code="a">Machine learning</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-ITC</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030738197</subfield></datafield></record></collection> |
| id | DE-604.BV045351543 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:15:43Z |
| institution | BVB |
| isbn | 9781785282980 1785282980 1785282581 9781785282584 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030738197 |
| oclc_num | 935744746 |
| open_access_boolean | |
| physical | 1 online resource illustrations |
| psigel | ZDB-4-ITC |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | Packt Publishing |
| record_format | marc |
| series2 | Community experience distilled |
| spelling | Ansari, Saleem Verfasser aut Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users Saleem Ansari Birmingham, UK Packt Publishing 2016 1 online resource illustrations txt rdacontent c rdamedia cr rdacarrier Community experience distilled Online resource; title from cover page (Safari, viewed January 21, 2016). - Includes index Learn to use Scala to build a recommendation engine from scratch and empower your website usersAbout This Book Learn the basics of a recommendation engine and its application in e-commerce Discover the tools and machine learning methods required to build a recommendation engine Explore different kinds of recommendation engines using Scala libraries such as MLib and SparkWho This Book Is ForThis book is written for those who want to learn the different tools in the Scala ecosystem to build a recommendation engine. No prior knowledge of Scala or recommendation engines is assumed. What You Will Learn Discover the tools in the Scala ecosystem Understand the challenges faced in e-commerce systems and learn how you can solve those challenges with a recommendation engine Familiarise yourself with machine learning algorithms provided by the Apache Spark framework Build different versions of recommendation engines from practical code examples Enhance the user experience by learning from user feedback Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendationsIn DetailWith an increase of data in online e-commerce systems, the challenges in assisting users with narrowing down their search have grown dramatically. The various tools available in the Scala ecosystem enable developers to build a processing pipeline to meet those challenges and create a recommendation system to accelerate business growth and leverage brand advocacy for your clients. This book provides you with the Scala knowledge you need to build a recommendation engine. You'll be introduced to Scala and other related tools to set the stage for the project and familiarise yourself with the different stages in the data processing pipeline, including at which stages you can leverage the power of Scala and related tools. You'll also discover different machine learning algorithms using MLLib. As the book progresses, you will gain detailed knowledge of what constitutes a collaborative filtering based recommendation and explore different methods to improve users' recommendation. Style and approachA step-by-step guide full of real-world, hands-on examples of Scala recommendation engines. Each example is placed in context with explanation and visuals COMPUTERS / Programming Languages / General bisacsh Functional programming languages fast Machine learning fast Scala (Computer program language) fast Scala (Computer program language) Functional programming languages Machine learning Erscheint auch als Druck-Ausgabe |
| spellingShingle | Ansari, Saleem Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users Learn to use Scala to build a recommendation engine from scratch and empower your website usersAbout This Book Learn the basics of a recommendation engine and its application in e-commerce Discover the tools and machine learning methods required to build a recommendation engine Explore different kinds of recommendation engines using Scala libraries such as MLib and SparkWho This Book Is ForThis book is written for those who want to learn the different tools in the Scala ecosystem to build a recommendation engine. No prior knowledge of Scala or recommendation engines is assumed. What You Will Learn Discover the tools in the Scala ecosystem Understand the challenges faced in e-commerce systems and learn how you can solve those challenges with a recommendation engine Familiarise yourself with machine learning algorithms provided by the Apache Spark framework Build different versions of recommendation engines from practical code examples Enhance the user experience by learning from user feedback Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendationsIn DetailWith an increase of data in online e-commerce systems, the challenges in assisting users with narrowing down their search have grown dramatically. The various tools available in the Scala ecosystem enable developers to build a processing pipeline to meet those challenges and create a recommendation system to accelerate business growth and leverage brand advocacy for your clients. This book provides you with the Scala knowledge you need to build a recommendation engine. You'll be introduced to Scala and other related tools to set the stage for the project and familiarise yourself with the different stages in the data processing pipeline, including at which stages you can leverage the power of Scala and related tools. You'll also discover different machine learning algorithms using MLLib. As the book progresses, you will gain detailed knowledge of what constitutes a collaborative filtering based recommendation and explore different methods to improve users' recommendation. Style and approachA step-by-step guide full of real-world, hands-on examples of Scala recommendation engines. Each example is placed in context with explanation and visuals COMPUTERS / Programming Languages / General bisacsh Functional programming languages fast Machine learning fast Scala (Computer program language) fast Scala (Computer program language) Functional programming languages Machine learning |
| title | Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users |
| title_auth | Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users |
| title_exact_search | Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users |
| title_full | Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users Saleem Ansari |
| title_fullStr | Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users Saleem Ansari |
| title_full_unstemmed | Building a recommendation engine with Scala learn to use Scala to build a recommendation engine from scratch and empower your website users Saleem Ansari |
| title_short | Building a recommendation engine with Scala |
| title_sort | building a recommendation engine with scala learn to use scala to build a recommendation engine from scratch and empower your website users |
| title_sub | learn to use Scala to build a recommendation engine from scratch and empower your website users |
| topic | COMPUTERS / Programming Languages / General bisacsh Functional programming languages fast Machine learning fast Scala (Computer program language) fast Scala (Computer program language) Functional programming languages Machine learning |
| topic_facet | COMPUTERS / Programming Languages / General Functional programming languages Machine learning Scala (Computer program language) Scala (Computer program language) Functional programming languages Machine learning |
| work_keys_str_mv | AT ansarisaleem buildingarecommendationenginewithscalalearntousescalatobuildarecommendationenginefromscratchandempoweryourwebsiteusers |