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所在平台: Udemy |
课程主页: https://www.udemy.com/course/clusteranalysis/
课程评论：没有评论
**课程名称：** Cluster Analysis: Unsupervised Machine Learning in Python (聚类分析：Python 中的无监督机器学习) **课程概述：** 本课程专注于无监督机器学习中的聚类分析技术。随着人工智能和机器学习日益融入日常生活，了解其底层原理至关重要。课程以 Google News 自动聚合新闻的例子引入，揭示了无监督学习在发现数据隐藏模式和分组中的作用。 学习者将深入了解几种主流的聚类技术，包括： * K-Means 聚类 * 层次聚类 (Hierarchical Clustering) * 均值漂移聚类 (Mean Shift Clustering) * DBSCAN (基于密度的噪声应用空间聚类) * OPTICS (排序点以识别聚类结构) * 谱聚类 (Spectral Clustering) 课程内容涵盖如何训练聚类模型、对数据进行聚类，以及利用性能指标评估和比较不同模型。通过完成本课程，学员将能够利用 Python 构建有效的聚类模型，从数据中提取有价值的见解。课程提供完整的 Python 程序和数据集供下载。 **职业发展：** 机器学习工程师被 Indeed 评为美国最佳职业之一，拥有 344% 的增长率和 146,085 美元的年薪中位数。整体而言，计算机和信息技术领域的就业前景广阔，预计在 2019 年至 2029 年间将增长 11%。 **学习目标：** * 理解无监督机器学习和聚类的基本概念。 * 熟练掌握 K-Means、层次聚类、DBSCAN 等常用聚类算法。 * 学习如何使用 Python 实现和应用这些聚类算法。 * 掌握评估聚类模型性能的方法。 * 能够独立构建机器学习模型进行数据聚类分析。
Artificial intelligence and machine learning are touching our everyday lives in more-and-more ways. There's an endless supply of industries and applications that machine learning can make more efficient and intelligent. You have probably come across Google News, which automatically groups similar news articles under a topic. Have you ever wondered what process runs in the background to arrive at these groups? Unsupervised machine learning is the underlying method behind a large part of this. Unsupervised machine learning algorithms analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without human intervention. This course introduces you to one of the prominent modelling families of Unsupervised Machine Learning called Clustering. This course provides the learners with the foundational knowledge to use Clustering models to create insights. You will become familiar with the most successful and widely used Clustering techniques, such as:K-Means ClusteringHierarchical ClusteringMean Shift ClusteringDBSCAN: Density-Based Spatial Clustering of Applications with NoiseOPTICS: Ordering points to identify the clustering structureSpectral ClusteringYou will learn how to train clustering models to cluster and use performance metrics to compare different models. By the end of this course, you will be able to build machine learning models to make clusters using your data. The complete Python programs and datasets included in the class are also available for download. This course is designed most straightforwardly to utilize your time wisely. Get ready to do more learning than your machine!Happy Learning.Career Growth:Employment website Indeed has listed machine learning engineers as #1 among The Best Jobs in the U.S., citing a 344% growth rate and a median salary of $146,085 per year. Overall, computer and information technology jobs are booming, with employment projected to grow 11% from 2019 to 2029.
