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scientific-computing #260
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建议有一两个初稿会比较好 |
是指稿件再修订两轮吗,目前内容都已经完成了
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Date: Tue, Jul 16, 2024 14:17 PM
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Subject: Re: [datawhalechina/DOPMC] scientific-computing (Issue #260)
建议有一两个初稿会比较好
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可以放出来,供大家参考 |
这个没问题,可以放
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From: ***@***.***>
Date: Tue, Jul 16, 2024 14:20 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [datawhalechina/DOPMC] scientific-computing (Issue #260)
是指稿件再修订两轮吗,目前内容都已经完成了
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可以放出来,供大家参考
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建议把初稿链接发出来~ |
原稿链接刚刚上传至我自己的gitee:https://gitee.com/ma-shituo/scientific-computing ,请查阅 |
同意 |
1 similar comment
同意 |
你好,已收到,谢谢。
|
7天内无反对意见则默认立项通过 |
你是否已经阅读并同意《Datawhale开源项目指南》?
你是否已经阅读并同意《Datawhale开源项目行为准则》?
项目简介
本项目主要介绍Python科学计算的内容。我们将Python常用的工具例如numpy,scipy,sympy,matplotlib,pandas,networkx,statsmodels,sklearn的常见用法进行了汇总与讲解。可以作为聪明办法学Python的下游课程,也可以作为数学建模导论的前置课程。我们致力于为大家带来更简洁的科学计算方法。
立项理由
Python语言作为一门通用性和专用性都很好的语言,由于其易学、开源受到程序员们的追捧。我在前面的工作里已经初步做好了Python数学建模导论的稿件,当然里面还有不少细节性问题正在修订ing。但是考虑到其中的知识密度高的有些硬核,我决定为它增加一门前置课程,就是现在你所看到的Python科学计算。
项目受众
对科学计算感兴趣的学生或工作党,学习数学建模导论课程觉得有些困难的同学
项目亮点
本项目相比于代码理论兼备的数学建模导论,知识密度更小,轻量化学起来更容易,内容实操性非常强,没有什么艰难的数学理论,所以对于纯动手的工科生更友好。
项目规划
目录:
负责人:若冰(马世拓)
进度:目前初稿已经完成
项目负责人
马世拓
https://github.com/ShituoMa
联系方式:[email protected]
备注:发起立项申请后DOPMC成员将会在7天内给出审核意见,若7天内无反对意见则默认立项通过~
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