Practical Machine Learning

开始时间: 07/04/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/practical-machine-learning

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课程详情

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

实用机器学习:数据科学家和数据分析师执行的最常见任务之一是预测和机器学习。本课程将涵盖构建和应用预测功能的基本组成部分,重点是实际应用。该课程将为概念提供基础知识,例如培训和测试集,过度拟合和错误率。本课程还将介绍一系列基于模型和算法的机器学习方法,包括回归,分类树,朴素贝叶斯和随机森林。该课程将涵盖构建预测功能的完整过程,包括数据收集,特征创建,算法和评估。

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课程简介

这门课程从数据科学的角度来应用机器学习进修实战,课程将会介绍机器学习的基础概念譬如训练集,测试集,过拟合和错误率等,同时这门课程也会介绍机器学习的基本模型和算法,例如回归,分类,朴素贝叶斯,以及随机森林。这门课程最终会覆盖一个完整的机器学习实战周期,包括数据采集,特征生成,机器学习算法应用以及结果评估等。

课程标签

机器学习 数据科学专项 机器学习实际 数据科学 机器学习实践 机器学习实战

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