Clojure for Data Science

Henry Garner

  • 出版商: Packt Publishing
  • 出版日期: 2015-09-04
  • 售價: $2,010
  • 貴賓價: 9.5$1,910
  • 語言: 英文
  • 頁數: 608
  • 裝訂: Paperback
  • ISBN: 1784397180
  • ISBN-13: 9781784397180
  • 相關分類: JVM 語言Data Science
  • 下單後立即進貨 (約3~4週)

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商品描述

Statistics, big data, and machine learning for Clojure programmers

About This Book

  • Write code using Clojure to harness the power of your data
  • Discover the libraries and frameworks that will help you succeed
  • A practical guide to understanding how the Clojure programming language can be used to derive insights from data

Who This Book Is For

This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether you're tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunities–and inform you of the risks–that exist in data of all shapes and sizes.

What You Will Learn

  • Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence
  • Implement the core machine learning techniques of regression, classification, clustering and recommendation
  • Understand the importance of the value of simple statistics and distributions in exploratory data analysis
  • Scale algorithms to web-sized datasets efficiently using distributed programming models on Hadoop and Spark
  • Apply suitable analytic approaches for text, graph, and time series data
  • Interpret the terminology that you will encounter in technical papers
  • Import libraries from other JVM languages such as Java and Scala
  • Communicate your findings clearly and convincingly to nontechnical colleagues

In Detail

The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs.

Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don't yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language's flexibility!

You'll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark's MapReduce and GraphX's BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models.

Above all, by following the explanations in this book, you'll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future.

Style and approach

This is a practical guide to data science that teaches theory by example through the libraries and frameworks accessible from the Clojure programming language.

商品描述(中文翻譯)

《統計學、大數據和機器學習:Clojure程式設計師的指南》

關於本書
- 使用Clojure編寫程式碼,發揮數據的力量
- 探索能幫助您成功的庫和框架
- 實用指南,了解如何使用Clojure編程語言從數據中獲取洞察力

適合閱讀對象
本書針對已經熟悉Clojure並且對於在數據科學領域中需要深入理解的廣度和深度感到不知所措的開發人員。無論您是負責交付特定分析項目,還是只是覺得您可以從數據中獲得更多價值,本書將激發您對於各種形式和大小的數據中存在的機會的靈感,並告知您相應的風險。

學習內容
- 進行假設檢驗,了解特徵選擇和統計顯著性,以自信地解釋結果
- 實施回歸、分類、聚類和推薦等核心機器學習技術
- 了解簡單統計和分佈在探索性數據分析中的重要性
- 使用Hadoop和Spark上的分佈式編程模型,高效地將算法擴展到網絡規模的數據集
- 適用於文本、圖形和時間序列數據的適當分析方法
- 解釋在技術論文中遇到的術語
- 從Java和Scala等其他JVM語言導入庫
- 將您的發現清晰而有說服力地傳達給非技術同事

詳細內容
“數據科學”一詞被廣泛用於定義這個新的職業,這個職業被期望能夠解釋龐大的數據集並將其轉化為改進的決策和性能。Clojure是一種強大的語言,它結合了腳本語言的互動性和編譯語言的速度。加上其豐富的本地庫生態系統和非常簡單且一致的函數式數據操作方法,這種方法與數學公式密切相關,使其成為滿足數據科學家多樣需求的理想、實用和靈活的語言。

本書將帶您從簡單的摘要統計到複雜的機器學習算法,展示了如何使用Clojure編程語言從數據中獲取洞察力。數據科學家通常會開創新的道路,您將看到如何利用Clojure的Java互操作能力來訪問Mahout和Mllib等尚未存在Clojure封裝的庫。即使是經驗豐富的Clojure開發人員也將對他們的語言的靈活性有更深入的了解!

您將學習如何將統計思維應用於自己的數據,並使用Clojure以技術和統計學上的可靠方式進行探索、分析和可視化。您還可以使用Incanter進行本地數據處理,使用ClojureScript呈現交互式可視化,並了解Hadoop和Spark的MapReduce和GraphX的BSP等分佈式平台如何解決大規模數據分析的挑戰,以及如何使用這些編程模型解釋算法。

最重要的是,通過遵循本書中的解釋,您將學習不僅如何使用數據科學領域中當前最先進的方法,還將了解為什麼這些方法有效,以便在該領域未來發展時能夠持續提高工作效率。

風格和方法
這是一本實用的數據科學指南,通過Clojure編程語言可訪問的庫和框架示例來教授理論。