KotiRyhmätKeskusteluLisääAjan henki
Etsi sivustolta
Tämä sivusto käyttää evästeitä palvelujen toimittamiseen, toiminnan parantamiseen, analytiikkaan ja (jos et ole kirjautunut sisään) mainostamiseen. Käyttämällä LibraryThingiä ilmaiset, että olet lukenut ja ymmärtänyt käyttöehdot ja yksityisyydensuojakäytännöt. Sivujen ja palveluiden käytön tulee olla näiden ehtojen ja käytäntöjen mukaista.

Tulokset Google Booksista

Pikkukuvaa napsauttamalla pääset Google Booksiin.

Ladataan...

Java for Data Science

Tekijä: Richard M. Reese

JäseniäKirja-arvostelujaSuosituimmuussijaKeskimääräinen arvioKeskustelut
15-1,367,480--
Examine the techniques and Java tools supporting the growing field of data scienceAbout This Book- Your entry ticket to the world of data science with the stability and power of Java- Explore, analyse, and visualize your data effectively using easy-to-follow examples- Make your Java applications more capable using machine learningWho This Book Is ForThis book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful.What You Will Learn- Understand the nature and key concepts used in the field of data science- Grasp how data is collected, cleaned, and processed- Become comfortable with key data analysis techniques- See specialized analysis techniques centered on machine learning- Master the effective visualization of your data- Work with the Java APIs and techniques used to perform data analysisIn DetailData science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation.The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book.Style and approachThis book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.… (lisätietoja)
-
Ladataan...

Kirjaudu LibraryThingiin nähdäksesi, pidätkö tästä kirjasta vai et.

Ei tämänhetkisiä Keskustelu-viestiketjuja tästä kirjasta.

Ei arvosteluja
ei arvosteluja | lisää arvostelu
Sinun täytyy kirjautua sisään voidaksesi muokata Yhteistä tietoa
Katso lisäohjeita Common Knowledge -sivuilta (englanniksi).
Teoksen kanoninen nimi
Alkuteoksen nimi
Teoksen muut nimet
Alkuperäinen julkaisuvuosi
Henkilöt/hahmot
Tärkeät paikat
Tärkeät tapahtumat
Kirjaan liittyvät elokuvat
Epigrafi (motto tai mietelause kirjan alussa)
Omistuskirjoitus
Ensimmäiset sanat
Sitaatit
Viimeiset sanat
Erotteluhuomautus
Julkaisutoimittajat
Kirjan kehujat
Alkuteoksen kieli
Kanoninen DDC/MDS
Kanoninen LCC

Viittaukset tähän teokseen muissa lähteissä.

Englanninkielinen Wikipedia

-

Examine the techniques and Java tools supporting the growing field of data scienceAbout This Book- Your entry ticket to the world of data science with the stability and power of Java- Explore, analyse, and visualize your data effectively using easy-to-follow examples- Make your Java applications more capable using machine learningWho This Book Is ForThis book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful.What You Will Learn- Understand the nature and key concepts used in the field of data science- Grasp how data is collected, cleaned, and processed- Become comfortable with key data analysis techniques- See specialized analysis techniques centered on machine learning- Master the effective visualization of your data- Work with the Java APIs and techniques used to perform data analysisIn DetailData science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation.The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book.Style and approachThis book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.

Kirjastojen kuvailuja ei löytynyt.

Kirjan kuvailu
Yhteenveto haiku-muodossa

Current Discussions

-

Suosituimmat kansikuvat

Pikalinkit

Arvio (tähdet)

Keskiarvo: Ei arvioita.

Oletko sinä tämä henkilö?

Tule LibraryThing-kirjailijaksi.

 

Lisätietoja | Ota yhteyttä | LibraryThing.com | Yksityisyyden suoja / Käyttöehdot | Apua/FAQ | Blogi | Kauppa | APIs | TinyCat | Perintökirjastot | Varhaiset kirja-arvostelijat | Yleistieto | 204,393,686 kirjaa! | Yläpalkki: Aina näkyvissä