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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-for-bi-part-4/
课程评论：没有评论
课程名称：数据分析的机器学习：无监督学习 课程概述：此课程是《机器学习与数据科学的完整视觉指南》的组成部分，该指南结合了 Maven Analytics 的所有四个机器学习课程。此课程是整个系列的第4部分，旨在帮助您建立扎实的机器学习基础知识。课程不需要编写代码，而是使用 Microsoft Excel 等用户友好的工具来阐明复杂主题，帮助您理解机器学习的工作原理及其背后的原因。 课程大纲： 1. **无监督机器学习简介** - 无监督学习的概念 - 常见的无监督技术 - 特征工程 - 无监督学习的工作流程 2. **聚类与分段** - 聚类基础 - K-Means 聚类 - WSS 和肘部图 - 层次聚类 - 解读树状图 3. **关联挖掘** - 关联挖掘基础 - Apriori 算法 - 购物篮分析 - 最小支持阈值 - 稀疏与多个项目集 - 马尔可夫链 4. **异常检测** - 异常检测基础 - 跨段异常 - 最近邻 - 时间序列异常 - 残差分布 5. **降维** - 降维基础 - 主成分分析（PCA） - Scree 图 - 高级技术 课程还包含独特演示和真实案例研究，以巩固关键概念。例如，您将看到 k-means 如何帮助识别客户细分、Apriori 如何用于购物篮分析和推荐引擎，以及异常检测如何发现跨段或时间序列数据集中的异常值。 如果您准备好为成功的数据科学职业奠定基础，这就是适合您的课程！加入后，您将获得以下资源： - 高质量的随需视频 - 无监督学习电子书 - 可下载的Excel项目文件 - 专家问答论坛 - 30天退款保证 快乐学习！- Josh M. (Maven Analytics 机器学习首席讲师)
HEADS UP! This course is now part of The Complete Visual Guide to Machine Learning & Data Science, which combines all 4 Machine Learning courses from Maven Analytics. This course, along with the other individual courses in the series, will be retired soon.This course is PART 4 of a 4-PART SERIES designed to help you build a strong, foundational understanding of Machine Learning:PART 1: QA & Data ProfilingPART 2: Classification ModelingPART 3: Regression & ForecastingPART 4: Unsupervised LearningThis course makes data science approachable to everyday people, and is designed to demystify powerful Machine Learning tools & techniques without trying to teach you a coding language at the same time.Instead, we'll use familiar, user-friendly tools like Microsoft Excel to break down complex topics and help you understand exactly HOW and WHY machine learning works before you dive into programming languages like Python or R. Unlike most Data Science and Machine Learning courses, you won't write a SINGLE LINE of code.COURSE OUTLINE:In this course, we'll start by reviewing the Machine Learning landscape, exploring the differences between Supervised and Unsupervised Learning, and introducing several of the most common unsupervised techniques, including cluster analysis, association mining, outlier detection, and dimensionality reduction.Throughout the course, we'll focus on breaking down each concept in plain and simple language to help you build an intuition for how these models actually work, from K-Means and Apriori to outlier detection, Principal Component Analysis, and more.Section 1: Intro to Unsupervised Machine LearningUnsupervised Learning LandscapeCommon Unsupervised TechniquesFeature EngineeringThe Unsupervised ML WorkflowSection 2: Clustering & SegmentationClustering BasicsK-Means ClusteringWSS & Elbow PlotsHierarchical ClusteringInterpreting a DendogramSection 3: Association MiningAssociation Mining BasicsThe Apriori AlgorithmBasket AnalysisMinimum Support ThresholdsInfrequent & Multiple Item SetsMarkov ChainsSection 4: Outlier DetectionOutlier Detection BasicsCross-Sectional OutliersNearest NeighborsTime-Series OutliersResidual DistributionSection 5: Dimensionality ReductionDimensionality Reduction BasicsPrinciple Component Analysis (PCA)Scree PlotsAdvanced TechniquesThroughout the course, we'll introduce unique demos and real-world case studies to help solidify key concepts along the way. You'll see how k-means can help identify customer segments, how apriori can be used for basket analysis and recommendation engines, and how outlier detection can spot anomalies in cross-sectional or time-series datasets.If you're ready to build the foundation for a successful career in Data Science, this is the course for you!__________Join today and get immediate, lifetime access to the following:High-quality, on-demand videoMachine Learning: Unsupervised Learning ebookDownloadable Excel project fileExpert Q & A forum30-day money-back guaranteeHappy learning!-Josh M. (Lead Machine Learning Instructor, Maven Analytics)__________Looking for our full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, and Tableau courses!See why our courses are among the TOP-RATED on Udemy:"Some of the BEST courses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen!" Russ C."This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier!" Tatsiana M."Maven Analytics should become the new standard for all courses taught on Udemy!" Jonah M.
