Machine Learning with Spark and Python: Essential Techniques for Predictive Analytics 2/e

Michael Bowles

商品描述

Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Spark--a ML framework from the Apache foundation. By implementing Spark, machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code.

Machine Learning with Spark and Python focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers many use cases such as what ad to place on a web page, predicting prices in securities markets, or detecting credit card fraud. The focus on two families gives enough room for full descriptions of the mechanisms at work in the algorithms. Then the code examples serve to illustrate the workings of the machinery with specific hackable code.

商品描述(中文翻譯)

《使用Spark和Python進行機器學習:預測分析的基本技術,第二版》通過專注於兩個關鍵算法,簡化了機器學習的實際應用。這本新的第二版增加了Apache基金會的ML框架Spark。通過實施Spark,機器學習學生可以輕鬆處理更大的數據集,並使用普通的Python代碼調用Spark算法。

《使用Spark和Python進行機器學習》專注於兩個算法家族(線性方法和集成方法),這些方法能夠有效地預測結果。這類問題涵蓋了許多用例,例如在網頁上放置廣告、預測證券市場的價格或檢測信用卡欺詐。專注於兩個家族為算法的工作機制提供了足夠的空間進行全面描述。然後,代碼示例用於演示具體的可編程代碼的運作方式。