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docs/.vuepress/components/ahome-footer.vue

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<div class="left-box item">
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<h4>👥兄弟文档</h4>
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<ul>
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<!-- <li>
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<a href="https://www.paddlepaddle.org.cn/?from=numpy-cn" target="_blank">PaddlePaddle 中文文档</a>
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</li> -->
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<li>
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<a href="https://megengine.org.cn/doc/stable/zh/getting-started/index.html?from=numpy-cn" target="_blank">MegEngine (๑•̀ㅂ•́)و 中文文档</a>
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</li>
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<li>
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<a href="https://www.pypandas.cn/" target="_blank">Pandas 中文网</a>
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</li>

docs/.vuepress/nav/zh.js

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text: '文章',
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link: '/article/'
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},
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// {
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// text: '深度学习',
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// link: '/deep/',
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// important: true
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// },
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{
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text: '深度学习',
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link: '/deep/',
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important: true
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},
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{
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text: '用户指南',
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link: '/user/'

docs/.vuepress/sidebar/deep_zh.js

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module.exports = function () {
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return [
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{
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title: '深度学习基础教程',
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title: '为深度学习新手准备的教程',
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collapsable: true,
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sidebarDepth: 3,
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children: [
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['/deep/basics/', '前言'],
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['/deep/basics/fit_a_line', '线性回归'],
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['/deep/basics/recognize_digits', '数字识别'],
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['/deep/basics/image_classification', '图像分类'],
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['/deep/basics/word2vec', '词向量'],
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['/deep/basics/recommender_system', '个性化推荐'],
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['/deep/basics/understand_sentiment', '情感分析'],
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['/deep/basics/label_semantic_roles', '语义角色标注'],
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['/deep/basics/machine_translation', '机器翻译'],
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['/deep/basics/gan', '生成对抗网络']
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]
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},
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{
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title: '七日入门深度学习',
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collapsable: true,
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sidebarDepth: 3,
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children: [
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['/deep/videos/day1_01', 'Day 1:初识深度学习'],
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['/deep/videos/day1_02', 'Day 1:如何快速入门深度学习?'],
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['/deep/videos/day2_01', 'Day 2:图像识别基础与实战'],
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['/deep/videos/day3_01', 'Day 3:目标检测基础与实践(一)'],
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['/deep/videos/day3_02', 'Day 3:目标检测实战-RCNN算法讲解'],
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['/deep/videos/day3_03', 'Day 3:目标检测实战-YOLOv3检测物体']
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['/deep/beginner/megengine_basic_concepts', '天元 MegEngine 基础概念'],
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['/deep/beginner/learning_from_linear_regression', '一个稍微复杂些的线性回归模型'],
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['/deep/beginner/from_linear_regression_to_linear_classification', '从线性回归到线性分类']
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]
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}
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]

docs/README.md

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heroImage: https://static.numpy.org.cn/site/logo.png
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actionText: 快速了解 →
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actionLink: /user/
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action2Text: 开始深度学习
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action2Link: https://megengine.org.cn/?from=numpy-cn
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footer: 署名-非商业性使用-相同方式共享 3.0 中国大陆 (CC BY-NC-SA 3.0 CN) | Copyright © 2019-present Zhi Bing
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---
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docs/deep/README.md

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---
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meta:
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- name: keywords
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content: NumPy,深度学习
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content: NumPy,深度学习,MegEngine
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- name: description
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content: 本栏目会指导你如何使用 NumPy、Matplotlib、Pandas 和 国产深度学习框架paddlepaddle 进行深度学习的入门。
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content: 本栏目会指导你如何使用 NumPy、Matplotlib、Pandas 和 国产深度学习框架 MegEngine 进行深度学习的入门。
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---
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# NumPy 与深度学习
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# NumPy 与 深度学习
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<a href="https://www.paddlepaddle.org.cn/?from=pandas-cn" target="_blank">
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<img src="https://static.numpy.org.cn/inside/9d3fe9e349990cba65902826dda16f11.png@w800h800">
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<p></p><p></p>
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<a href="https://megengine.org.cn/?from=numpy-cn" target="_blank">
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<img src="https://static.numpy.org.cn/inside/megengin_0001.png">
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</a>
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<p></p><p></p>
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欢迎来到 NumPy 与深度学习栏目!
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本栏目会指导你如何使用 [NumPy](https://www.numpy.org.cn/)[Matplotlib](https://www.matplotlib.org.cn/)[Pandas](https://www.pypandas.cn/) 和 国产深度学习框架[paddlepaddle](https://www.paddlepaddle.org.cn/?from=pandas-cn) 进行深度学习的入门。
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本栏目会指导你如何使用 [NumPy](https://www.numpy.org.cn/)[Matplotlib](https://www.matplotlib.org.cn/)[Pandas](https://www.pypandas.cn/) 和 国产深度学习框架[MegEngine](https://megengine.org.cn/?from=numpy-cn) 进行深度学习的入门。
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## 为深度学习新手准备的教程目录
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- [天元 MegEngine 基础概念](/deep/beginner/megengine_basic_concepts.html)
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- [一个稍微复杂些的线性回归模型](/deep/beginner/learning_from_linear_regression.html)
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- [从线性回归到线性分类](/deep/beginner/from_linear_regression_to_linear_classification.html)

docs/deep/basics/README.md

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