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23 lines
1.5 KiB
23 lines
1.5 KiB
# 机器学习入门
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课程的本章节将为您介绍机器学习领域背后的基本概念、什么是机器学习,并学习它的历史以及曾为此做出贡献的技术研究者们。让我们一起开始探索机器学习的全新世界吧!
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![globe](../images/globe.jpg)
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> 图片由 <a href="https://unsplash.com/@bill_oxford?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Bill Oxford</a>提供,来自 <a href="https://unsplash.com/s/photos/globe?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
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### 课程安排
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1. [机器学习简介](../1-intro-to-ML/translations/README.zh-cn.md)
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1. [机器学习的历史](../2-history-of-ML/translations/README.zh-cn.md)
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1. [机器学习中的公平性](../3-fairness/translations/README.zh-cn.md)
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1. [机器学习技术](../4-techniques-of-ML/translations/README.zh-cn.md)
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### 致谢
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"机器学习简介"由 [Muhammad Sakib Khan Inan](https://twitter.com/Sakibinan), [Ornella Altunyan](https://twitter.com/ornelladotcom) 及 [Jen Looper](https://twitter.com/jenlooper),共同倾 ♥️ 而作
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"机器学习及人工智能历史" 由 [Jen Looper](https://twitter.com/jenlooper) 及 [Amy Boyd](https://twitter.com/AmyKateNicho)倾 ♥️ 而作
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"公平性与机器学习" 由 [Tomomi Imura](https://twitter.com/girliemac) 倾 ♥️ 而作
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"机器学习的技术" 由 [Jen Looper](https://twitter.com/jenlooper) 及 [Chris Noring](https://twitter.com/softchris) 倾 ♥️ 而作
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