人工智能基础：机器学习.
(eVideo)
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Format
eVideo
Language
chi
Notes
General Note
3/18/202112:00:00AM
Participants/Performers
Presenter: Doug Rose
Description
学习如何使用机器学习做出更好的决策，在数据中找到模式。
Description
机器学习是人工智能中最活跃的领域之一。机器学习算法使计算机无需编程即可学习新事物。计算机使用统计数据来更好地理解我们每天生成的海量数据。这些新算法可以帮助机器对图像、声音和视频进行分类。它们可以解答我们的问题、发现新药物，甚至写歌。在本课程中，我们介绍了机器学习的定义和类型：监督、无监督和强化。然后了解如何使用决策树、聚类和回归分析等热门的算法来查看海量数据集中的模式。最后我们将了解开始使用机器学习时，会遇到哪些陷阱。
System Details
Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.
Citations
APA Citation, 7th Edition (style guide)
Rose, D. (2021). 人工智能基础：机器学习 . linkedin.com.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Rose, Doug. 2021. 人工智能基础：机器学习. linkedin.com.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Rose, Doug. 人工智能基础：机器学习 linkedin.com, 2021.
MLA Citation, 9th Edition (style guide)Rose, Doug. 人工智能基础：机器学习 linkedin.com, 2021.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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Grouped Work ID
4f969df3-20f0-e52a-e3e3-2a8968232858-chi
Grouping Information
| Grouped Work ID | 4f969df3-20f0-e52a-e3e3-2a8968232858-chi |
|---|---|
| Full title | 人工智能基础 机器学习 |
| Author | rose doug |
| Grouping Category | movie |
| Last Update | 2022-07-12 21:21:31PM |
| Last Indexed | 2024-05-04 02:26:41AM |
Book Cover Information
| Image Source | sideload |
|---|---|
| First Loaded | Jul 13, 2021 |
| Last Used | Feb 28, 2024 |
Marc Record
| First Detected | Mar 23, 2021 12:00:00 AM |
|---|---|
| Last File Modification Time | Aug 03, 2021 03:57:52 AM |
MARC Record
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| 520 | |a 机器学习是人工智能中最活跃的领域之一。机器学习算法使计算机无需编程即可学习新事物。计算机使用统计数据来更好地理解我们每天生成的海量数据。这些新算法可以帮助机器对图像、声音和视频进行分类。它们可以解答我们的问题、发现新药物，甚至写歌。在本课程中，我们介绍了机器学习的定义和类型：监督、无监督和强化。然后了解如何使用决策树、聚类和回归分析等热门的算法来查看海量数据集中的模式。最后我们将了解开始使用机器学习时，会遇到哪些陷阱。 | ||
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