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ml

这是一些常见机器学习算法例子,可单独运行,也是自己学习机器学习过程中实践的一些代码,有些理解整理了网上一些资料,后面还会陆续添加一些实战代码与深度学习的例子。
一些学习心得体会欢迎访问我的博客:http://blog.csdn.net/meihao5
自己的学习经历如下:
《机器学习导论》,美国人写的一本书,完全文字描述,没有不懂的高大上公式,导论书特别推荐,其中对集成学习,计算学习的理论阐述,其它地方都没见到过这样通俗 易懂的描述
李航老师的《统计学习方法》,看了好几遍,每一遍都有收获,适合对机器学习有一些了解的,然后理解推到其中原理,较为详细。
周志华老师的《机器学习》,虽然周老师说是入门书籍,其中真的不简单,内容全面,适合有一定基础的同学看,最好补一些数学知识。
吴恩达大牛的机器学习课程,还有最近开的深度学习课程,网上都可以找到翻译过的视频,结合笔记学习,真的非常棒,
然后零零碎碎从一些博客中学习各种深度学习模型.
NLP文件夹下,是一份自然语言处理非常好的英文资料,是哥伦比亚大学的NLP课程讲义,我也还在学习中,(知乎上面一个大牛分享的~)

当然啦,实践才能更为深刻理解公式啦,所以,还有多敲代码。

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