[Udemy, Henrik Johansson] Master Cluster Analysis with Python and Pandas [2025] [9/2024, ENG]

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LearnJavaScript Beggom · 26-Июл-25 20:44 (3 месяца 29 дней назад)

Master Cluster Analysis with Python and Pandas [2025]
Год выпуска: 9/2024
Производитель: Udemy
Сайт производителя: https://www.udemy.com/course/master-cluster-analysis-with-python-and-pandas/
Автор: Henrik Johansson
Продолжительность: 26h 41m 45s
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. Master Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logic
  10. Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling
  11. Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
  12. Manipulate data and use advanced multi-dimensional uneven data structures
  13. Master the Pandas 2 and 3 library for Advanced Data Handling
  14. Use the language and fundamental concepts of the Pandas library and handle all aspects of creating, modifying, and selecting Data from a Pandas DataFrame
  15. Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
  16. Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data
  17. Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data
  18. [Extra Video] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn
  19. 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. Programming experience is not needed and you will be taught everything you need
  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 with Pandas and Python!
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 3-in-1 master class video course about mastering Cluster Analysis and Unsupervised Learning with Advanced Data Handling using the Python 3 programming language combined with the powerful Pandas 2 + 3 library.
You will be taught to master some of the most useful and powerful Cluster Analysis and unsupervised learning techniques available and you will learn to master the Python programming language and the Pandas library for advanced Data Handling.
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. Master Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logic
  10. Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling
  11. Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
  12. Manipulate data and use advanced multi-dimensional uneven data structures
  13. Master the Pandas 2 and 3 library for Advanced Data Handling
  14. Use the language and fundamental concepts of the Pandas library and handle all aspects of creating, changing, modifying, and selecting Data from a Pandas DataFrame object
  15. Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
  16. Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data
  17. Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data
  18. [Extra Video] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn
  19. Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
  20. Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
  21. 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.
  22. And much more…
This course is an excellent way to learn to master Cluster Analysis, Unsupervised Learning, Python, Pandas and Advanced Data Handling!
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.
Data Handling is the process of making data useful for analysis. Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks. Mastering Data Handling with Python and Pandas is an extremely useful and time-saving skill that functions as a force multiplier for productivity.
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
  2. learn to Master Python 3 from scratch or the beginner level
  3. learn to Master Python 3 and knows another programming language
  4. reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
  5. learn to Master the Pandas library
  6. learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career
  7. learn advanced Data Handling and improve their capabilities and productivity
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. Programming experience is not needed and you will be taught everything you need
  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, Unsupervised Learning, Python, Pandas, and Data Handling.
Enroll now to receive 25+ 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 Master Cluster Analysis and Unsupervised Learning
  2. Everyone who wants to Master Python 3 from scratch or the beginner level
  3. Everyone who wants to Master Python 3 and knows another programming language
  4. Everyone who wants to reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
  5. Everyone who wants to Master the Pandas library
  6. Everyone who wants to learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career
  7. Everyone who wants to learn advanced Data Handling and improve their capabilities and productivity
Формат видео: MP4
Видео: avc, 1920x1080, 16:9, 30.000 к/с, 1294 кб/с
Аудио: aac lc sbr, 48.0 кгц, 62.7 кб/с, 2 аудио
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Recorded date : 2024-09-26 01:45:07.1465787-07:00
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