Udemy
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
Development
Web Development Data Science Mobile Development Programming Languages Game Development Database Design & Development Software Testing Software Engineering Development Tools No-Code Development
Business
Entrepreneurship Communications Management Sales Business Strategy Operations Project Management Business Law Business Analytics & Intelligence Human Resources Industry E-Commerce Media Real Estate Other Business
Finance & Accounting
Accounting & Bookkeeping Compliance Cryptocurrency & Blockchain Economics Finance Finance Cert & Exam Prep Financial Modeling & Analysis Investing & Trading Money Management Tools Taxes Other Finance & Accounting
IT & Software
IT Certification Network & Security Hardware Operating Systems Other IT & Software
Office Productivity
Microsoft Apple Google SAP Oracle Other Office Productivity
Personal Development
Personal Transformation Personal Productivity Leadership Career Development Parenting & Relationships Happiness Esoteric Practices Religion & Spirituality Personal Brand Building Creativity Influence Self Esteem & Confidence Stress Management Memory & Study Skills Motivation Other Personal Development
Design
Web Design Graphic Design & Illustration Design Tools User Experience Design Game Design Design Thinking 3D & Animation Fashion Design Architectural Design Interior Design Other Design
Marketing
Digital Marketing Search Engine Optimization Social Media Marketing Branding Marketing Fundamentals Marketing Analytics & Automation Public Relations Advertising Video & Mobile Marketing Content Marketing Growth Hacking Affiliate Marketing Product Marketing Other Marketing
Lifestyle
Arts & Crafts Beauty & Makeup Esoteric Practices Food & Beverage Gaming Home Improvement Pet Care & Training Travel Other Lifestyle
Photography & Video
Digital Photography Photography Portrait Photography Photography Tools Commercial Photography Video Design Other Photography & Video
Health & Fitness
Fitness General Health Sports Nutrition Yoga Mental Health Dieting Self Defense Safety & First Aid Dance Meditation Other Health & Fitness
Music
Instruments Music Production Music Fundamentals Vocal Music Techniques Music Software Other Music
Teaching & Academics
Engineering Humanities Math Science Online Education Social Science Language Teacher Training Test Prep Other Teaching & Academics
AWS Certification Microsoft Certification AWS Certified Solutions Architect - Associate AWS Certified Cloud Practitioner CompTIA A+ Cisco CCNA Amazon AWS CompTIA Security+ Microsoft AZ-900
Photoshop Graphic Design Adobe Illustrator Drawing Digital Painting InDesign Character Design Canva Figure Drawing
Life Coach Training Neuro-Linguistic Programming Mindfulness Personal Development Personal Transformation Meditation Life Purpose Coaching Neuroscience
Web Development JavaScript React CSS Angular PHP WordPress Node.Js Python
Google Flutter Android Development iOS Development Swift React Native Dart Programming Language Mobile Development Kotlin SwiftUI
Digital Marketing Google Ads (Adwords) Social Media Marketing Google Ads (AdWords) Certification Marketing Strategy Internet Marketing YouTube Marketing Email Marketing Retargeting
SQL Microsoft Power BI Tableau Business Analysis Business Intelligence MySQL Data Analysis Data Modeling Big Data
Business Fundamentals Entrepreneurship Fundamentals Business Strategy Online Business Business Plan Startup Freelancing Blogging Home Business
Unity Game Development Fundamentals Unreal Engine C# 3D Game Development C++ 2D Game Development Unreal Engine Blueprints Blender
2020-12-27 18:14:25
30-Day Money-Back Guarantee

This course includes:

  • 4.5 hours on-demand video
  • 19 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Data Science Cluster Analysis

Cluster Analysis & Unsupervised Machine Learning in R

Harness Power of R for unsupervised machine Learning (k-means, hierarchical clustering) - With Practical Examples in R
Rating: 4.9 out of 54.9 (8 ratings)
1,638 students
Created by Kate Alison, Georg Müller
Last updated 12/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Your complete guide to unsupervised learning and clustering using R-programming language
  • It covers both theoretical background of UNSUPERVISED MACHINE LERANING as well as practical examples in R and R-Studio
  • Fully understand the basics of Machine Learning, Cluster Analysis & Unsupervised Machine Learning
  • Highly practical data science examples related to unsupervised machine learning and clustering
  • Be Able To Harness The Power Of R For Practical Data Science
  • You will have a glimpse on the power of cloud computimg with Google services (i.e. Earth Engine)
  • It covers a real-world application of K-means clustering for mapping tasks in UAE
  • Improve your R-programming and JavaScript coding skills
  • Implement Unsupervised Clustering Techniques Such As k-means Clustering and Hierarchical Clustering
  • Apply your newly learned skills to your independent project
  • Evaluate Model Performance & Learn The Best Practices For Evaluating Machine Learning Model Accuracy
  • Learn R-programming from scratch: R crash course is included that you could start R-programming for machine learning

Course content

10 sections • 41 lectures • 4h 27m total length

  • Preview02:33
  • What is Machine Leraning and it's main types?
    09:27
  • Overview of Machine Leraning in R
    01:40

  • Preview02:43
  • How to install R and RStudio in 2020
    05:33
  • Lab: Get started with R in RStudio
    09:37
  • Sign up for Google Earth Engine (needed for your projects later in the course)
    03:37
  • Interface of Google Earth Engine: Code Editor & Explorer
    08:56

  • Introduction
    01:04
  • Lab: Installing Packages and Package Management in R
    04:19
  • Preview01:45
  • Overview of data types and data structures in R
    08:19
  • Lab: data types and data structures in R
    09:57
  • Dataframes: overview
    03:21
  • Functions in R - overview
    08:27
  • Lab: Functions in R - get started!
    04:11
  • Lab: For Loops in R
    03:56
  • Read Data into R
    05:13

  • Unsupervised Learning & Clustering: theory
    05:30
  • Hierarchical Clustering: Example
    07:34
  • Preview02:07
  • Hierarchical Clustering: Merging points
    02:39
  • Heat Maps: theory
    08:32
  • Heat Maps: Lab
    04:30

  • K-Means Clustering: Theory
    04:53
  • Example K-Means Clustering in R: Lab
    05:31
  • K-means clustering: Application to email marketing
    14:35
  • Heatmaps to visualize K-Means Results in R: Examplery Lab
    04:22
  • Model-based Unsupervised Clustering in R
    10:33

  • Starting with Fuzzy K-means in R
    14:34
  • Entropy Weighted K-Means in R
    09:19

  • How to assess a Clustering Tendency of the dataset
    05:27
  • Selecting the number of clusters for unsupervised Clustering methods (K-Means)
    09:33
  • Assessing the performance of unsupervised learning (clustering) algorithms
    07:17
  • How to compare the performance of different unsupervised clustering algoritms?
    05:27

  • Introduction to Case Study
    07:19
  • Project Assignment
    09:58

  • Understanding using satellite images for mapping tasks: short introduction
    06:59
  • Import images and their visualization in Earth Engine
    16:11
  • Unsupervised K-means satellite image analysis in Earth Engine for mapping
    08:34

  • Bonus Lecture
    01:04

Requirements

  • Availabiliy computer and internet
  • R-programming skills is NOT a requirement, but would be a plus

Description

HERE IS WHY YOU SHOULD TAKE THIS COURSE:

This course will be your complete guide to unsupervised learning and clustering using R-programming language and JavaScript.

Unlike other courses, it offers NOT ONLY the guided demonstrations of the R-scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY UNSUPERVISED MACHINE LEARNING  (K-means, Hierarchical clustering) in R.

This course also covers all the main aspects of practical and highly applied data science related to unsupervised machine learning and clustering techniques. Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based data science domain.

In this age of big data, companies across the globe use R and Google Cloud Computing Services to analyze big volumes of data for business and research. By becoming proficient in unsupervised learning in R, you can give your company a competitive edge and boost your career to the next level. In addition, you will have a chance to test the power of cloud computing with Google services (i.e. Earth Engine) for a real-world application of unsupervised K-means learning for mapping applications.

THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF UNSUPERVISED MACHINE LEARNING: THEORY & PRACTISE

- Fully understand the basics of Machine Learning, Cluster Analysis & Unsupervised Machine Learning from theory to practice

- Harness applications of unsupervised learning (cluster analysis) in R and with Google Cloud Services

- Machine Learning, Supervised Learning, Unsupervised Learning in R

- Complete two independent projects on Unsupervised Machine Learning in R and using Google Cloud Services

- Implement Unsupervised Clustering Techniques (k-means Clustering and Hierarchical Clustering etc)

- and MORE

NO PRIOR R OR STATISTICS/MACHINE LEARNING / R KNOWLEDGE REQUIRED:

You’ll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

My course will help you implement the methods using real data obtained from different sources, including implementing a real-life project on the cloud computing platform of Google. Thus, after completing my unsupervised data clustering course in R, you’ll easily use different data streams and data science packages to work with real data in R.

I will also provide you with the all scripts and data used in the course.

In case it is your first encounter with R, don’t worry, my course a full introduction to the R & R-programming in this course.

This course is different from other training resources. Each lecture seeks to enhance your data science and clustering skills (K-means, Hierarchical clustering, weighted-K means, Heat mapping, etc) in a demonstrable and easy-to-follow manner and provide you with practically implementable solutions. You’ll be able to start analyzing different streams of data for your projects and gain appreciation from your future employers with your improved machine learning skills and knowledge of the cutting edge data science methods.

The course is ideal for professionals who need to use cluster analysis, unsupervised machine learning, and R in their field.

One important part of the course is the practical exercises. You will be given some precise instructions and datasets to run Machine Learning algorithms using the R and Google Cloud Computing tools.

JOIN MY COURSE NOW!


Who this course is for:

  • The course is ideal for professionals who need to use cluster analysis, unsupervised machine learning and R in their field.
  • Everyone who would like to learn Data Science Applications In The R & R Studio Environment
  • Everyone who would like to learn theory and implementation of Unsupervised Learning On Real-World Data

Instructors

Kate Alison
Remote Sensing/GIS Expert & Data Scientist
Kate Alison
  • 4.3 Instructor Rating
  • 805 Reviews
  • 25,991 Students
  • 20 Courses

I am a passionate data scientist, Earth Observation (EO), and GIS expert and educator. I received my M.Sc. in Earth Observation and applied data science from the University of Southampton (United Kingdom) and I also hold a Ph.D. Degree in EO from Germany. I do regular teaching and training all over the world as well as do regularly consultancies on the mentioned topic. I have thousands of satisfied clients all over the world! And now I will be glad if I can teach also you these interesting, highly applied, and exciting topics!


For GIS & Remote Sensing students:

If you would like to learn comprehensively geospatial data analysis, here is a preferred order for how to take my courses:

Option 1: Take all individual courses that have more details on specific subjects, more lectures, and more labs in the following order:

1. Get started with GIS & Remote Sensing in QGIS #Beginners

2. Remote Sensing in QGIS: Fundamentals of Image Analysis 2020

3. Core GIS: Land Use and Land Cover & Change Detection in QGIS

4. Machine Learning in GIS: Understand the Theory and Practice

5. Machine Learning in GIS: Land Use/Land Cover Image Analysis

6. Machine Learning in ArcGIS: Map Land Use/ Land Cover in GIS

7. Object-based image analysis & classification in QGIS/ArcGIS

8. ArcGIS: Learn Deep Learning in ArcGIS to advance GIS skills

8. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1

10. Google Earth Engine for Machine Learning & Change Detection

Option 2: Take my ‘joint’ courses that contain summarized information from the above courses, though in fewer details (labs, videos):

1. Geospatial Data Analyses & Remote Sensing: 4 Classes in 1

2. Machine Learning in GIS and Remote Sensing: 5 Courses in 1

3. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1

4. Google Earth Engine for Machine Learning & Change Detection


For Data Science & Machine Learning Students:

1. R Crash Course - Introduction to R / RStudio / R-programming

2. Get started with R -Introduction to R-programming #Beginners (FREE)

3. R - Cluster Analysis & Unsupervised Machine Learning in R

Georg Müller
Data Science Experte
Georg Müller
  • 4.5 Instructor Rating
  • 186 Reviews
  • 10,261 Students
  • 8 Courses

Ich bin ein erfahrener Berater und Experte in Data Science. Ich habe mein MSc in Informatik an der TH Köln und MBA an der Universität Durham (UK) erlangt und habe mich später im Fachbereich Informatik promoviert. Als erfahrene Trainer mit mehr als 15 Jahren Berufserfahrung möchte ich meine Leidenschaft, praktische Erfahrungen und Kenntnisse in den Themen Big Data, Data Science, Data Analytics und IT management mit den anderen teilen und die praktische Kompetenzen von meinen Studenten auf ein sehr hohes Niveau bringen.

  • Udemy for Business
  • Teach on Udemy
  • Get the app
  • About us
  • Contact us
  • Careers
  • Blog
  • Help and Support
  • Affiliate
  • Terms
  • Privacy policy
  • Cookie settings
  • Sitemap
  • Featured courses
Udemy
© 2021 Udemy, Inc.