Java for Data Science
暫譯: 數據科學中的 Java

Richard M. Reese, Jennifer L. Reese

  • 出版商: Packt Publishing
  • 出版日期: 2017-01-12
  • 定價: $1,620
  • 售價: 6.0$972
  • 語言: 英文
  • 頁數: 386
  • 裝訂: Paperback
  • ISBN: 1785280112
  • ISBN-13: 9781785280115
  • 相關分類: Java 程式語言Data Science
  • 立即出貨 (庫存 < 3)

商品描述

Examine the techniques and Java tools supporting the growing field of data science

About 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 learning

Who This Book Is For

This 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 analysis

In Detail

Data 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 approach

This 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.

商品描述(中文翻譯)

檢視支援不斷增長的資料科學領域的技術和 Java 工具

關於本書



  • 您進入資料科學世界的入場券,搭配 Java 的穩定性和強大功能

  • 使用易於跟隨的範例有效探索、分析和視覺化您的資料

  • 利用機器學習使您的 Java 應用程式更具能力

本書適合誰閱讀


本書適合那些熟悉使用 Java 開發應用程式的 Java 開發者。希望進入資料科學領域或希望建立智能應用程式的人將會發現本書非常理想。渴望成為資料科學家的讀者也會覺得本書非常有幫助。

您將學到什麼



  • 了解資料科學領域的本質和關鍵概念

  • 掌握資料的收集、清理和處理方式

  • 熟悉關鍵的資料分析技術

  • 了解以機器學習為中心的專門分析技術

  • 掌握有效的資料視覺化技巧

  • 使用 Java API 和技術進行資料分析

詳細內容


資料科學關注於從各種資料來源中提取知識和見解,以分析模式或預測未來行為。它涉及統計學、計算機科學、數學、機器學習和資料挖掘等多個學科。在本書中,我們涵蓋了重要的資料科學概念及其如何受到 Java 的支援,以及通常在統計上具有挑戰性的技術,以便讓您理解其目的和應用。


本書首先介紹資料科學,接著是資料收集、資料清理、資料分析和資料視覺化的基本資料科學任務。然後討論統計技術和更高級的主題,包括機器學習、神經網絡和深度學習。接下來的部分檢視資料分析的主要類別,包括文本、視覺和音頻資料,並討論支援平行實作的資源。


最後一章展示了一個深入的資料科學問題,並提供了一個全面的基於 Java 的解決方案。由於主題的性質,簡單的技術範例會在前面呈現,隨後在書中會有更詳細的處理。這樣可以更自然地介紹書中所呈現的技術和概念。

風格與方法


本書採用教程式的方法,提供每個主要概念的範例。


以逐步指導的風格,本書涵蓋資料科學的各個面向,並將幫助您快速上手。