机器学习中的支持向量机算法应用

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支持向量机的PAI平台实现

支持向量机的PAI平台实现

认证
支持向量机的PAI平台实现

支持向量机的PAI平台实现

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课程视频时间

44 分钟
语言

英文
课程类型

线上

USD 10.00

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课程介绍

SVM（支持向量机）是最好的“现成”监督学习算法之一，可用于回归和分类任务。它被广泛用于分类目标。支持向量机（SVM）是由分离超平面正式定义的判别分类器。换句话说，给定标记的训练数据（监督学习），算法输出最佳超平面，其对新示例进行分类。在二维空间中，这个超平面是将平面分成两部分的线，其中每一级都位于两侧。本课程介绍了SVM的基本概念，以及如何使用阿里云机器学习平台进行PAI应用SVM。

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有机器学习和数据库经验的工程师

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1购买认证

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考试

认证:

Apsara Clouder—大数据：支持向量机的PAI平台实现
考试类型：

线上
语言:

英文
考试时间：

30 分钟
考试机会：

2次

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支持向量机的PAI平台实现

通过本课程，您将学习什么是SVM(支持向量机)以及如何使用阿里云机器学习平台实现SVM。

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课程内容简介
SVM理论（上）
SVM理论（下）
SVM应用演示
课程回顾

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