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AI and Machine Learning

AI and Machine Learning

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Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses

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๐Ÿ“ˆ Analytical overview of Telegram channel AI and Machine Learning

Channel AI and Machine Learning (@machine_learning_courses) in the English language segment is an active participant. Currently, the community unites 94 144 subscribers, ranking 1 548 in the Education category and 2 998 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 94 144 subscribers.

According to the latest data from 28 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 939 over the last 30 days and by 37 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 7.03%. Within the first 24 hours after publication, content typically collects 2.49% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 6 622 views. Within the first day, a publication typically gains 2 343 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
  • Thematic interests: Content is focused on key topics such as learning, llm, linkedin, linux, udemy.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œLearn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_coursesโ€

Thanks to the high frequency of updates (latest data received on 29 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

94 144
Subscribers
+3724 hours
+2867 days
+93930 days
Posts Archive
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๐Ÿ“ฆ Exercice Files

Machine Learning and AI Foundations: Advanced Decision Trees with KNIME @Linkedin_Learning

๐Ÿ”ธ Full description ๐Ÿ”ธ Every year, it seems, there is a new hot trend in data science. One of the hottest predictive analytics algorithms this year is gradient-boosted trees. One cannot hope to understand why it is popular and successful if one doesnt understand the basics of decision trees. Specific tree algorithms have risen and fallen in popularity, but the core concepts have been fundamental to the discipline for at least 30 years. In this course, instructor Keith McCormick demonstrates and discusses a half-dozen popular decision tree algorithms. Keith shows how to access them using other open-source options from within the KNIME platform. He explains them and reverse engineers them to create a solid foundation on which to build more advanced data science skills.

๐Ÿ”… Machine Learning and AI Foundations: Advanced Decision Trees with KNIME ๐Ÿ”Š Author: Keith McCormick ๐Ÿ”ธ Date: 2022-11-14 โฐ D
๐Ÿ”… Machine Learning and AI Foundations: Advanced Decision Trees with KNIME ๐Ÿ”Š Author: Keith McCormick ๐Ÿ”ธ Date: 2022-11-14 โฐ Duration: 1h 33m ๐ŸŒ€ Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform. ๐Ÿ“— Topics: Decision Trees, Knime, Machine Learning ๐Ÿ”ท Join @linkedin_learning for more courses

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19 Appendix - NumPy - Part 02.zip239.76 MB