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所在平台: Udemy |
课程主页: https://www.udemy.com/course/unsupervised-machine-learning-from-first-principles/
课程评论：没有评论
Coursera 课程《从第一性原理出发的无监督机器学习》 **课程概述：** 随着当今数据量的爆炸式增长，我们每天都在产生海量的数据。例如，平均每秒钟谷歌处理超过 40,000 次搜索，每分钟就有超过 50 万张照片在 Snapchat 上分享。这些数据绝大多数是无结构化的，无法直接使用传统的监督学习方法进行分析。本课程专注于从第一性原理的角度，深入讲解无监督机器学习的核心概念和技术，旨在帮助学习者理解如何在实际应用中分析非结构化数据。课程内容侧重于概念理解而非代码实现，以使学习者能够灵活运用所学知识。课程内容与监督学习之间也存在紧密联系，许多无监督学习技术（如聚类）在探索性数据分析（EDA）中扮演着重要角色。 **课程内容来源：** 本课程的教学内容来源于多个权威资源，包括： * 讲师在 Udemy 上的《从第一性原理出发的监督机器学习》课程。 * 《统计学习导论》（Introduction to Statistical Learning）教材。 * 《使用 Python 进行无监督机器学习实战：从无标签数据构建机器学习解决方案》（Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data）教材（强烈推荐购买）。 * 《统计学习要素》（Elements of Statistical Learning）教材。 * 各种学术文章和期刊论文。
There are some interesting statistics regarding how much data is being generated every day, including:There are 2.5 quintillion bytes of data created each day at our current paceOver the last two years alone 90 percent of the data in the world was generatedOn average, Google now processes more than 40,000 searches EVERY second (3.5 billion searches per day)Every minute of the day, Snapchat users share 527,760 photos, more than 120 professionals join LinkedIn, users watch 4,146,600 YouTube videos, 456,000 tweets are sent on Twitter, Instagram users post 46,740 photos and there are 510,000 comments posted and 293,000 statuses updated on FacebookThis data explosion has fueled the need for data scientists and inviduals who can analyse it. The problem is most of that data is unstructured. There is no format to it and so a different set on techniques from the common Supervised Learning are required to analyse it. Those techniques are taught in this course from a First Principles perspective. It is not about the code but the understanding of the concepts of Unsupervised Learning in order to apply them in the real world. What I have actually come to realise is the connection between supervised and unsupervised learning. When doing your Exploratory Data Analysis (EDA), you will probably make use of the techniques discussed in this course, for example Clustering.The content discussed in this course will be from different sources including:My "Supervised Machine Learning Course From First Principles" course here on Udemy,Introduction to Statistical Learning textbookAttribution for the core content is given to the textbook "Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" which I would urge you to buy on AmazonElements of Statistical Learning textbookDifferent articles and journal papers.
