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Data Science & Machine Learning Free Resources

Data Science & Machine Learning Free Resources

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The learning community for Data Science, Machine Learning and AI šŸ¤– 1) Data Science 2) Machine Learning 3) Data viz 4) Artificial Intelligence 5) Python 6) Ebooks 7) Articles 8) Free Courses

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šŸ“ˆ Analytical overview of Telegram channel Data Science & Machine Learning Free Resources

Channel Data Science & Machine Learning Free Resources (@datascience69) in the English language segment is an active participant. Currently, the community unites 20 445 subscribers, ranking 9 861 in the Education category and 19 981 in the India region.

šŸ“Š Audience metrics and dynamics

Since its creation on невіГомо, the project has demonstrated rapid growth, gathering an audience of 20 445 subscribers.

According to the latest data from 27 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -58 over the last 30 days and by -8 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 1.48%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 303 views. Within the first day, a publication typically gains 0 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
  • Thematic interests: Content is focused on key topics such as learning, dataset, selection, algorithm, analytic.

šŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
ā€œThe learning community for Data Science, Machine Learning and AI šŸ¤– 1) Data Science 2) Machine Learning 3) Data viz 4) Artificial Intelligence 5) Python 6) Ebooks 7) Articles 8) Free Coursesā€

Thanks to the high frequency of updates (latest data received on 28 October, 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.

20 445
Subscribers
-824 hours
-37 days
-5830 days
Posts Archive
Machine Learning Visualisation from basics to advanced

Implementation of Logistic Regression in Jupyter Note Book.pdf2.84 MB

Supervised_Machine_Learning_for_Text_Analysis_in_R_Emil_Hvitfeldt.pdf16.14 MB

Quantum_machine_learning_what_quantum_computing_means_to_data_mining.pdf27.95 MB

Probability for data SciencešŸ’”.pdf8.83 MB

Successful Algorithmic Trading Michael L. Halls-Moore, 2015

šŸ‘‰šŸ» DO REACT IF YOU WANT MORE CONTENT LIKE THIS FOR FREE šŸ†“

HANDSON_DATA_SCIENCE_AND_PYTHON_MACHINE_LEARNING_@computer_books.pdf17.56 MB