Spark plugs

Spark plugs

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怎样用spark机器学习使用户数据可视化?-技术开发专区 首页 手机 笔记本平板 家电厨卫 数码音频 diy整机 企业it 服务器 网络通信 存储 网络安全 虚拟化 数据中心 无线组网 企业商用 技术开发 信息化 云计算 大数据 办公 办公频道 打印机 复合机 投影机 d打印 耗材 互动 chinaunix itpub社区 it文库 数据库大会 架构师大会 社区 本友会 机友会 索尼论坛 技术开发 频道 it 首页 > 技术开发 > 技术开发方案 > 正文 怎样用spark机器学习使用户数据可视化?
在第一部分中,我们将探索使用spark机器学习数据管道进行情感分析。我们将使用一个amazon产品评论数据集,并构建一个机器学习模型来将评论分为正面和负面。 在这篇文章中,我们将讨论以下内容: 分类和情感分析概念概述 从文本文档构建特征向量 训练机器学习模型,使用逻辑回归对正面和负面评论进行分类 评估和保存机器学习模型 分类 分类是受监督的机器学习算法,其基于标记数据(诸如电子邮件主题和消息文本)来识别项目属于哪个类别(例如电子邮件是否是垃圾邮件)。 用于分类的一些常见用例包括信用卡欺诈检测,电子邮件垃圾邮件检测和情绪分析。...
http://tech.it168.com/a2019/0520/5169/000005169824.shtml
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in the st century with the... read more tags: ai , azure event hubs , azure ml , azure sphere , cosmos db , data science , iot , machine learning deep learning without labels ★★★★★ ★★★★ ★★★ ★★ ★ october , october , by ml blog team // comments announcing new open source contributions to the apache spark
community for creating deep, distributed, object detectors – without a single human-generated label this post is authored by members of the microsoft ml for apache spark team – mark hamilton, minsoo thigpen, abhiram eswaran, ari green, courtney cochrane, janhavi suresh mahajan, karthik rajendran, sudarshan...
https://blogs.technet.microsoft.com/machinelearning/