106 lines
6.0 KiB
Markdown
106 lines
6.0 KiB
Markdown
## Background
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This project is a summary of the author's years of study and work practice.
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Most of the code has been actually run to ensure accuracy.
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本项目是作者多年学习与工作实践的总结,绝大部分代码都经过实际运行保证准确无误
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## Structure
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```
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-- bigdata solution for bigdata,contains hive/hadoop/spark/hbase etc...
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-- code-languages programming language,contains java/python/scala etc...
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-- cs-other some interesting things in the cs field
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-- deep-learning derivation of some algorithm principles of deep learning,tensorflow frame etc...
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-- feature-engineering feature-engineering is very important for algorithm
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-- math mathematical principles,contains matrix analysis, probability and statistics etc...
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-- mathcasebycase some mathematical knowledge points that are relatively scattered and difficult to classify
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-- recommend knowledge about recommendation system
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-- service-enginnering service online,essential knowledge for algorithm online
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-- tools various tools commonly used in practice,
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including awk, grep, sed data processing three swordsmen,
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git, maven and other common tools, intellij,
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sublime, vim and other IDEs,
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linux-shell common scripts
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-- traditional-algorithm traditional machine learning algorithms that are different from deep learning,
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including clustering algorithms/optimization methods/tree algorithms, etc.,
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as well as a brief introduction to mllib.
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```
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```
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-- bigdata 大数据处理方案,包括hive/hadoop/spark/hbase等
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-- code-languages 编码语言,包括java/python/scala等
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-- cs-other cs领域的一些有意思的事情
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-- deep-learning 深度学习的一些算法原理推导,tensorflow等框架
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-- feature-engineering 特征工程,做过算法的人都知道特征工程重要性
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-- math 数学原理,包括矩阵分析,概率统计等算法中常用数学知识
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-- mathcasebycase 一些比较分散不好归类的数学知识点
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-- recommend 推荐系统一些相关知识,目前作者就从事推荐相关工作
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-- service-enginnering 线上服务,算法上线必备知识
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-- tools 实际中常用的各种工具,包括awk,grep,sed数据处理三剑客,git,maven等常见工具,
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intellij,sublime,vim等IDE, linux-shell常见脚本
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-- traditional-algorithm 区别于深度学习的传统机器学习算法,包括聚类算法/最优化方法/树类算法等,
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还有mllib的简单介绍。
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```
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## Suitable for
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### for computer science guys
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The author come from a non-CS major,
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and did not systematically study data structures, operating systems,
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design patterns and other courses during school.
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The relevant knowledge is to be studied systematically after work.
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So this project is especially suitable for non-CS majors.
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作者非CS专业科班出身,在校期间并未系统学习过数据结构,操作系统,设计模式等课程,
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相关的知识都是工作以后再进行系统学习。
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所以该项目特别适合非CS专业同学参考。
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### for non-computer science guys
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For CS majors, some of them have not studied mathematics courses systematically,
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such as matrix analysis, probability statistics, optimization, etc.
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The major of the author's master's degree is pattern recognition.
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And in the future work, he roughly understand which mathematical knowledge
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is the key and difficult point in algorithm learning and practice.
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Therefore, this project is also suitable for students majoring in CS
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CS专业的同学,有一部分没有系统学过数学方面的课程,比如矩阵分析,概率统计,最优化等。
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作者硕士阶段所学专业为模式识别,在以后的工作中,
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大致了解哪些数学知识是算法学习与实践中的重点与难点。
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因此,该项目也特别适合CS专业的同学。
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### for guys who need to put the algorithm online from 0 to 1
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The algorithm is not just an offline train model,
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it can even be said that the offline train model is only a small part of the work.
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On the contrary, the corresponding engineering capabilities,
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code capabilities, and data capabilities are very important.
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Therefore, this project is especially suitable for guys
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who need to put the algorithm online from 0 to 1.
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算法并不只是离线train model,甚至可以说离线train model只是工作很小的一部分。
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相反对应的工程能力,代码能力,数据能力非常重要。
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因此该项目特别适合需要将算法从0到1怼上线的同学
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### for guys who need to solve various practical problems in actual work
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The project not only contains algorithm theory, algorithm derivation,
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but also more engineering and data aspects.
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Most of them are actual problems encountered in work,
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which can provide you with reference ideas in practice.
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Therefore, this project is especially suitable for guys
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who need to solve various practical problems in actual combat.
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该项目不仅有算法理论,算法推导,还有更多工程以及数据方面的内容,
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大部分都是工作中遇到的实际问题,可以为大家实践中提供参考思路。
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因此该项目特别适合实战中需要解决各种实际问题的同学
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## CSDN address
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https://blog.csdn.net/bitcarmanlee
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## Update
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The layout and stability of github is higher than that of csdn.
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In the future, it will be prioritized to maintain the projects on github,
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and csdn will also keep synchronized updates.
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github的排版以及稳定性比csdn更高,以后优先维护github上的项目,CSDN也会保持同步更新。
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