[Udemy, Henrik Johansson] Master Cluster Analysis and Unsupervised Learning [2025] [9/2024, ENG]

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LearnJavaScript Beggom · 26-Июл-25 17:40 (4 месяца 8 дней назад)

Master Cluster Analysis and Unsupervised Learning [2025]
Год выпуска: 9/2024
Производитель: Udemy
Сайт производителя: https://www.udemy.com/course/master-cluster-analysis-and-unsupervised-learning/
Автор: Henrik Johansson
Продолжительность: 5h 26m 59s
Тип раздаваемого материала: Видеоурок
Язык: Английский
Субтитры: Английский
Описание:
What you'll learn
  1. Master Cluster Analysis and Unsupervised Learning both in theory and practice
  2. Master simple and advanced Cluster Analysis models
  3. Use K-means Cluster Analysis, DBSCAN, Hierarchical Cluster models, Principal Component Analysis, and more…
  4. Evaluate Cluster Analysis models using many different tools
  5. Learn advanced Unsupervised and Supervised Learning theory and be introduced to auto-updated Simulations
  6. Gain Understanding of concepts such as truth, predicted truth or model-based conditional truth
  7. Use effective advanced graphical tools to judge models’ performance
  8. Use the Scikit-learn libraries for Cluster Analysis and Unsupervised Learning, supported by Matplotlib, Seaborn, Pandas, and Python
  9. Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
Requirements
  1. Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
  2. Access to a computer with an internet connection
  3. Some Python skill is necessary and some experience with the Pandas library is recommended
  4. The course only uses costless software
  5. Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
Description
Welcome to the course Master Cluster Analysis and Unsupervised Learning!
Cluster Analysis and Unsupervised learning are one of the most important and defining tasks within machine learning and data science. Cluster Analysis and Unsupervised learning are one of the main methods for data scientists, analysts, A.I., and machine intelligences to create new insights, information or knowledge from data.
This course is a practical and exciting hands-on master class video course about mastering Cluster Analysis and Unsupervised Learning.
You will be taught to master some of the most useful and powerful Cluster Analysis and unsupervised learning techniques available...
You will learn to:
  1. Master Cluster Analysis and Unsupervised Learning both in theory and practice
  2. Master simple and advanced Cluster Analysis models
  3. Use K-means Cluster Analysis, DBSCAN, Hierarchical Cluster models, Principal Component Analysis, and more…
  4. Evaluate Cluster Analysis models using many different tools
  5. Learn advanced Unsupervised and Supervised Learning theory and be introduced to auto-updated Simulations
  6. Gain Understanding of concepts such as truth, predicted truth or model-based conditional truth
  7. Use effective advanced graphical tools to judge models’ performance
  8. Use the Scikit-learn libraries for Cluster Analysis and Unsupervised Learning, supported by Matplotlib, Seaborn, Pandas, and Python
  9. Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
  10. Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
  11. Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.
  12. And much more…
This course is an excellent way to learn to master Cluster Analysis and Unsupervised Learning!
Cluster Analysis and Unsupervised Learning are considered exploratory types of data analysis and are useful for discovering new information and knowledge. Unsupervised Learning and Cluster Analysis are often viewed as one of the few ways for artificial intelligences and machine intelligences to create new knowledge or data information without human assistance or supervision, so-called supervised learning.
This course provides you with the option to use Cloud Computing with the Anaconda Cloud Notebook and to learn to use Cloud Computing resources, or you may use any Python capable environment of your choice.
This course is designed for everyone who wants to
  1. learn to Master Cluster Analysis and Unsupervised Learning
Requirements:
  1. Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
  2. Access to a computer with an internet connection
  3. Some Python skill is necessary and some experience with the Pandas library is recommended
  4. The course only uses costless software
  5. Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Cluster Analysis, and Unsupervised Learning.
Enroll now to receive 5+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!
Who this course is for:
  1. Everyone who wants to learn to Master Cluster Analysis and Unsupervised Learning
Формат видео: MP4
Видео: avc, 1920x1080, 16:9, 30.000 к/с, 2189 кб/с
Аудио: aac lc sbr, 48.0 кгц, 62.7 кб/с, 2 аудио
MediaInfo
General
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File size : 379 MiB
Duration : 22 min 30 s
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Overall bit rate : 2 354 kb/s
Frame rate : 30.000 FPS
Recorded date : 2024-10-18 19:41:59.6389817-07:00
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Frame rate : 30.000 FPS
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Codec configuration box : avcC
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Commercial name : HE-AAC
Format settings : Implicit
Codec ID : mp4a-40-2
Duration : 22 min 30 s
Bit rate mode : Variable
Bit rate : 62.7 kb/s
Maximum bit rate : 64.0 kb/s
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Channel layout : L R
Sampling rate : 48.0 kHz
Frame rate : 23.438 FPS (2048 SPF)
Compression mode : Lossy
Stream size : 10.1 MiB (3%)
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Alternate group : 1
Скриншоты
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