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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/the-nuts-and-bolts-of-machine-learning
课程评论：没有评论
课程名称：《机器学习的基本概念与实践》 课程概述：本课程是谷歌高级数据分析证书的第六门课程，旨在教授机器学习的基本知识，帮助学员理解如何运用算法和统计学使计算机系统从数据中发现模式。数据专业人士运用机器学习分析大量数据、解决复杂问题并做出准确预测。课程主要聚焦于机器学习的两种主要类型：监督学习和无监督学习。 课程大纲： 1. 机器学习的不同类型：学习机器学习的基本概念及其在数据科学中的作用，回顾四种主要的机器学习类型：监督学习、无监督学习、强化学习和深度学习。 2. 构建复杂模型的工作流程：了解数据专业人士如何使用结构化的机器学习工作流程，识别每个步骤的重要性，并学习如何将特定的机器学习模型应用于商业问题。 3. 无监督学习技术：深入探讨无监督学习，了解监督学习与无监督学习的区别，以及各自的优缺点，学习如何应用两种无监督机器学习模型：聚类分析与K均值算法。 4. 基于树的建模：聚焦于监督学习，学习如何测试和验证监督机器学习模型的表现，例如决策树、随机森林和梯度提升法。 5. 课程结束项目：完成最终的课程项目，通过将不同的机器学习模型应用于工作场景数据集，巩固所学知识。 通过本课程，学员将能掌握机器学习的核心概念与应用，为后续的数据分析与决策提供有力支持。
Name:The different types of machine learning
Description:You’ll start by exploring the basic concepts of machine learning and the role of machine learning in data science. Then, you’ll review the four main types of machine learning: supervised, unsupervised, reinforcement, and deep learning.
Name:Workflow for building complex models
Description:You’ll learn how data professionals use a structured workflow for machine learning. You'll identify the main steps of the workflow and the importance of each step in the overall process. Then, you'll learn how to apply specific machine learning models to business problems.
Name:Unsupervised learning techniques
Description:You’ll learn more about one of the major types of machine learning: unsupervised learning. You'll begin by exploring the difference between supervised and unsupervised techniques and the benefits and uses of each approach. Then, you’ll learn how to apply two unsupervised machine learning models: clustering and K-means.
Name:Tree-based modeling
Description:Next, you’ll focus on supervised learning. You’ll learn how to test and validate the performance of supervised machine learning models such as decision tree, random forest, and gradient boosting.
Name:Course 6 end-of-course project
Description:You’ll complete the final end-of-course project by applying different machine learning models to a workplace scenario dataset.
This is the sixth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn about machine learning, which uses algorithms and statistics to teach computer systems to discover patterns in data. Data professionals use machine learning to help analyze large amounts of data, solve complex problems, and make accurate predictions. You’ll focus on the two main types of machine learning: supervised and unsupervised. You'll learn how to apply different machine learn
