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Data Science & Machine Learning

Data Science & Machine Learning

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The first channel on Telegram that offers exciting questions, answers, and tests in data science, artificial intelligence, machine learning, and programming languages. For promotions: @love_data

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πŸ“ˆ Analytical overview of Telegram channel Data Science & Machine Learning

Channel Data Science & Machine Learning (@datascienceinterviews) in the English language segment is an active participant. Currently, the community unites 27 635 subscribers, ranking 6 985 in the Education category and 14 704 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 27 635 subscribers.

According to the latest data from 01 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 198 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.40%. Within the first 24 hours after publication, content typically collects 0.48% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 664 views. Within the first day, a publication typically gains 133 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 5.
  • Thematic interests: Content is focused on key topics such as insidead, mining, pinix, learning, neo.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œThe first channel on Telegram that offers exciting questions, answers, and tests in data science, artificial intelligence, machine learning, and programming languages. For promotions: @love_data”

Thanks to the high frequency of updates (latest data received on 02 September, 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.

27 635
Subscribers
+224 hours
+547 days
+19830 days
Posts Archive
23. Recommender Systems.zip64.58 MB

22. Principal Component Analysis.zip41.72 MB

21. K Means Clustering.zip82.38 MB

20. Support Vector Machines.zip80.98 MB

19. Decision Trees and Random Forests.zip106.22 MB

18. K Nearest Neighbors.zip99.89 MB

17. Logistic Regression.zip124.29 MB

16. Cross Validation and Bias-Variance Trade-Off.zip10.26 MB

15. Linear Regression.zip105.10 MB

14. Introduction to Machine Learning.zip166.80 MB

13. Data Capstone Project.zip194.87 MB

12. Python for Data Visualization - Geographical Plotting.zip89.30 MB

11. Python for Data Visualization - Plotly and Cufflinks.zip55.88 MB

10_Python_for_Data_Visualization_Pandas_Built_in_Data_Visualization.zip57.55 MB

9. Python for Data Visualization - Seaborn.zip173.60 MB

8. Python for Data Visualization - Matplotlib.zip123.77 MB

7. Python for Data Analysis - Pandas Exercises.zip83.85 MB

6. Python for Data Analysis - Pandas.zip207.69 MB

5. Python for Data Analysis - NumPy.zip127.40 MB

4. Python Crash Course.zip140.43 MB