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GitHub
1 年
ML.02.md
机器学习需要的理论基础:数学,线性代数,数理统计,概率论,高等数学、凸优化理论,形式逻辑等. 1.学习准备. 数学内容的复习,高中数学、概率、线性代数等部分内容. Python基础语法学习. Google的TensorFlow深度学习开源框架. 2.Google的TensorFlow开源深度学习框架 ...
GitHub
5 年
# Linux的进程、线程、文件描述符是什么
**《labuladong 的算法秘籍》、《labuladong 的刷题笔记》两本 PDF 和刷题插件 2.0 免费开放下载,详情见 [labuladong 的刷题三件套 ...
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