foochane / Books
Licence: apache-2.0
整理一些书籍 ,包含 C&C++ 、git 、Java、Keras 、Linux 、NLP 、Python 、Scala 、TensorFlow 、大数据 、推荐系统、数据库、数据挖掘 、机器学习 、深度学习 、算法等。
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整理一些书籍
书籍目录如下：
│
├─01-C&C++
│ C和指针.pdf
│ C语言库函数使用大全.pdf
│ Effective C++第2版(中文版).pdf
│ Thinking C++.pdf
│
├─02-Java
│ Java开发手册.pdf
│ Java程序员修炼之道.pdf
│ Java编程思想(第4版).pdf
│
├─03-Python
│ Head_First_Python（中文版）.pdf
│ Python参考手册(第4版).pdf
│ Python源码剖析.pdf
│ 流畅的python.pdf
│ 用Python写网络爬虫.pdf
│ 精通Python设计模式.pdf
│
├─04-Scala
│ 快学Scala.pdf
│
├─05-Linux
│ Linux 内核0.11 完全注释-1.9.5.pdf
│ Linux与UNIX Shell编程指南.pdf
│ UNIX环境高级编程.pdf
│
├─06-Git
│ learn-github-from-zero.pdf
│
├─07-LaTeX
│ LaTeX入门(刘海洋).pdf
│ 一份不太简短的LATEX介绍.pdf
│
├─08-Keras
│ Python深度学习.pdf
│
├─09-TensorFlow
│ Practical Python AI Projects.pdf
│ Pro Deep Learning with TensorFlow.pdf
│ TensorFlow for Deep Learning.pdf
│ TensorFlow Machine Learning Cookbook.pdf
│ Tensorflow 实战Google深度学习框架.pdf
│ tensorflow-internals.pdf
│ TensorFlow实战_黄文坚.pdf
│ 面向机器智能的TensorFlow实践 (智能系统与技术丛书)_.pdf
│
├─10-机器学习
│ Machine Learning Applications Using Python.pdf
│ Machine Learning with TensorFlow.pdf
│ Practical Machine Learning with Python.pdf
│ 叶斯思维：统计建模的Python学习法.pdf
│ 机器学习(周志华).pdf
│ 机器学习实战-中文版.pdf
│ 机器学习导论.pdf
│ 模式识别与机器学习(中文).pdf
│ 深度学习21天实战Caffe.pdf
│ 百面机器学习.pdf
│ 统计学习方法(李航).pdf
│ 集体智慧编程中文版.pdf
│
├─11-深度学习
│ Deep Learning with Python (Nikhil Ketkar).pdf
│ Deep Learning with Python(François Chollet).pdf
│ Neural Network and Deep Learning(中文版).pdf
│ 一份简短的深度学习笔记(朱鉴).pdf
│ 动⼿学深度学习.pdf
│ 深度学习(中文版).pdf
│ 神经网络与机器学习(Simon Haykin).pdf
│ 神经网络与深度学习(邱锡鹏).pdf
│
├─12-NLP
│ Deep Learning for Natural Language Processing.pdf
│ NLP汉语自然语言处理原理与实践.pdf
│ PYTHON自然语言处理中文版.pdf
│ 统计自然语言处理基础(中文版).pdf
│
├─13-大数据
│ Learning PySpark.pdf
│ Machine Learning with PySpark.pdf
│ Machine Learning with Spark.pdf
│ PySpark实战指南：利用Python和Spark构建数据密集型应用并规模化部署.pdf
│ Spark for Data Science.pdf
│ Spark快速大数据分析.pdf
│ Spark机器学习.pdf
│ 自己动手做大数据系统.pdf
│
├─14-数据挖掘
│ Python数据分析与挖掘实战.pdf
│ 利用Python进行数据分析.pdf
│ 数据挖掘与数据化运营实战_思路_方法_技巧与应用_完整版.pdf
│ 数据挖掘应用20个案例分析.pdf
│ 数据挖掘：概念与技术（中文第三版）.pdf
│ 面向程序员的数据挖掘指南.pdf
│
├─15-推荐系统
│ Learning-to-rank.pdf
│ Recommender Systems Handbook.pdf
│ 推荐系统实践.pdf
│
├─16-数据库
│ MySQL网络数据库指南.pdf
│
├─17-算法
│ 剑指OFFER(第2版).pdf
│ 算法图解.pdf
│ 算法导论中文版.pdf
│
└─18-技术相关
不止代码.pdf
学习之道（美）乔希·维茨金.pdf
数学之美.pdf
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