10最好的无人监督的机器学习教程推荐

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特写 iPhone，显示 Udemy 应用程序和带笔记本的笔记本电脑有数以千计的在线课程和课程可以帮助您提高 无人监督的机器学习 技能并获得 无人监督的机器学习 证书。

在这篇博客文章中，我们的专家汇总了 10 个精选列表 最好的 无人监督的机器学习 课程, 现在在线提供的教程、培训计划、课程和认证。

我们只包括那些符合我们高质量标准的课程。我们花了很多时间和精力来为您收集这些。这些课程适合所有级别的初学者、中级学习者和专家。

以下是这些课程以及它们为您提供的内容！

10最好的无人监督的机器学习教程推荐

课程名 在校生（人数） 评论（计数）
1. Unsupervised Machine Learning Hidden Markov Models in Python 我们的最佳选择 24433+ 3438+
2. Cluster Analysis and Unsupervised Machine Learning in Python 23559+ 4520+
3. Unsupervised Machine Learning : With 2 Capstone ML Projects 13425+ 62+
4. K-Means for Cluster Analysis and Unsupervised Learning in R 5032+ 42+
5. Cluster Analysis & Unsupervised Machine Learning in R 4634+ 31+
6. K-Means for Cluster Analysis and Unsupervised Learning 2480+ 35+
7. Machine Learning for Data Analysis: Unsupervised Learning 1018+ 115+
8. Data Science-Unsupervised Machine Learning Using R 948+ 54+
9. Mastering Unsupervised Learning with Python 204+ 19+
10. Unsupervised Machine Learning with Python 167+ 12+

1. Unsupervised Machine Learning Hidden Markov Models in Python 经过 “Lazy Programmer Team, Lazy Programmer Inc.” Udemy课程 我们的最佳选择

“HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.”

截至目前，超过 24433+ 人们已经注册了这门课程，而且已经结束了 3438+ 评论.

课程内容
“Introduction and Outline
Markov Models
Markov Models: Example Problems and Applications
Hidden Markov Models for Discrete Observations
Discrete HMMs Using Deep Learning Libraries
HMMs for Continuous Observations
HMMs for Classification
Bonus Example: Parts-of-Speech Tagging
Theano, Tensorflow, and Machine Learning Basics Review
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale”

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2. Cluster Analysis and Unsupervised Machine Learning in Python 经过 “Lazy Programmer Team, Lazy Programmer Inc.” Udemy课程

“Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.”

截至目前，超过 23559+ 人们已经注册了这门课程，而且已经结束了 4520+ 评论.

课程内容
Introduction to Unsupervised Learning
K-Means Clustering
Hierarchical Clustering
Gaussian Mixture Models (GMMs)
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale

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3. Unsupervised Machine Learning : With 2 Capstone ML Projects 经过 Data Is Good Academy Udemy课程

Learn Complete Unsupervised ML: Clustering Analysis and Dimensionality Reduction

截至目前，超过 13425+ 人们已经注册了这门课程，而且已经结束了 62+ 评论.

课程内容
Introduction to Clustering Analysis
Introduction to Dimensionality Reduction
Optimizing Crop Production
Customer Segmentation Engine
Outro Section
Bonus Section

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4. K-Means for Cluster Analysis and Unsupervised Learning in R 经过 Kate Alison Udemy课程

The powerful K-Means Clustering Algorithm for Cluster Analysis and Unsupervised Machine Learning in R

截至目前，超过 5032+ 人们已经注册了这门课程，而且已经结束了 42+ 评论.

课程内容
Introduction
Software used in this course
R Crash Course – get started with R-programming in R-Studio
Unsupervised learning: K-Means in R: Theory & Practise
Advanced K-Means Clustering Analysis
Performance Evaluation of Unsupervised Learning CLustering Algorithms in R
Your Independent Project in K-Means CLuster Analysis
BONUS

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5. Cluster Analysis & Unsupervised Machine Learning in R 经过 “Kate Alison, Georg Müller” Udemy课程

“Harness Power of R for unsupervised machine Learning (k-means, hierarchical clustering) – With Practical Examples in R”

截至目前，超过 4634+ 人们已经注册了这门课程，而且已经结束了 31+ 评论.

课程内容
Introduction
Software used in this course
R Crash Course – get started with R-programming in R-Studio
Unsupervised learning: Hierarchical Clustering in R
Unsupervised Learning: K-Means Clustering
More Unsupervised Clustering techniques: Hands-On
Performance Evaluation of Unsupervised Learning Clustering Algorithms in R
Independent Project in Cluster Analysis based on Case Study
Applied Example: unsupervised K-means learning for mapping applications
Bonus

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6. K-Means for Cluster Analysis and Unsupervised Learning 经过 Hannes Hinrichs Udemy课程

The powerful K-Means Clustering Algorithm for Cluster Analysis and Unsupervised Machine Learning in Python

截至目前，超过 2480+ 人们已经注册了这门课程，而且已经结束了 35+ 评论.

课程内容
Introduction
The Mechanics of K-Means
Application: Implementation
Final words

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7. Machine Learning for Data Analysis: Unsupervised Learning 经过 “Maven Analytics, Joshua MacCarty” Udemy课程

Machine Learning made simple with Excel! Unsupervised learning topics for advanced data analysis & business intelligence

截至目前，超过 1018+ 人们已经注册了这门课程，而且已经结束了 115+ 评论.

课程内容
Getting Started
Intro to Unsupervised ML
Clustering & Segmentation
Association Mining & Basket Analysis
Outlier Detection
Dimensionality Reduction
Wrapping Up

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8. Data Science-Unsupervised Machine Learning Using R 经过 ExcelR Solutions Udemy课程

“Recommender Systems, Association Rules, Dimension Reduction, Network Analysis”

截至目前，超过 948+ 人们已经注册了这门课程，而且已经结束了 54+ 评论.

课程内容
Data Mining-Unsupervised Learning Using R
Recommender Systems
Association Rules
Dimension Reduction
Network Analysis

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9. Mastering Unsupervised Learning with Python 经过 Packt Publishing Udemy课程

“Master advanced clustering, topic modeling, manifold learning, and autoencoders using Python”

截至目前，超过 204+ 人们已经注册了这门课程，而且已经结束了 19+ 评论.

课程内容
Advanced Clustering Methods: Selecting the Best Algorithm
Topic Modeling: Semantic Content Recommendations
Manifold and Deep Learning for High-Dimensional Data

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10. Unsupervised Machine Learning with Python 经过 Satish Reddy Udemy课程

Unsupervised Machine Learning Clustering and Dimension Reduction Algorithms with Python Implementation and Applications

截至目前，超过 167+ 人们已经注册了这门课程，而且已经结束了 12+ 评论.

课程内容
Introduction
Python Demos
Review of Mathematical Concepts
Hierarchical Clustering
DBSCAN Clustering
K Means Clustering
Gaussian Mixture Model Clustering
Comparison of Clustering Algorithms
Dimension Reduction
Case Studies
Concluding Remarks and Thank You
Optional

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