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内容简介

  《机器学习实战》机器学习是人工智能研究领域中的一个极其重要的方向。在现今大数据时代的背景下,捕获数据并从中萃取有价值的信息或模式,使得这一过去为分析师与数学家所专属的研究领域越来越为人们瞩目。《机器学习实战》通过精心编排的实例,切入日常工作任务,摒弃学术化语言,利用高效可复用的Python代码阐释如何处理统计数据,进行数据分析及可视化。读者可从中学到一些核心的机器学习算法,并将其运用于某些策略性任务中,如分类、预测及推荐等。
  《机器学习实战》适合机器学习相关研究人员及互联网从业人员学习参考。

编辑推荐

《机器学习实战》面向日常任务的高效实战内容,介绍并实现机器学习的主流算法。《机器学习实战》没有从理论角度来揭示机器学习算法背后的数学原理,而是通过“原理简述+问题实例+实际代码+运行效果”来介绍每一个算法。学习计算机的人都知道,计算机是一门实践学科,没有真正实现运行,很难真正理解算法的精髓。这本书的好处就是边学边用,非常适合于急需迈进机器学习领域的人员学习。实际上,即使对于那些对机器学习有所了解的人来说,通过代码实现也能进一步加深对机器学习算法的理解。
《机器学习实战》的代码采用Python语言编写。Python代码简单优雅、易于上手,科学计算软件包众多,已经成为不少大学和研究机构进行计算机教学和科学计算的语言。相信Python编写的机器学习代码也能让读者尽快领略到这门学科的精妙之处。

作者简介

Peter Harrington 拥有电气工程学士和硕士学位,他曾经在美国加州和中国的英特尔公司工作7年。Peter拥有5项美国专利,在三种学术期刊上发表过文章。他现在是Zillabyte公司的首席科学家,在加入该公司之前,他曾担任2年的机器学习软件顾问。Peter在业余时间还参加编程竞赛和建造3D打印机。

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