Available now! Telegram Research 2025 โ the year's key insights 
Data Science & Machine Learning
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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data
Show more๐ Analytical overview of Telegram channel Data Science & Machine Learning
Channel Data Science & Machine Learning (@datasciencefun) in the English language segment is an active participant. Currently, the community unites 75 730 subscribers, ranking 2 116 in the Education category and 4 343 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 75 730 subscribers.
According to the latest data from 13 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 954 over the last 30 days and by 41 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.60%. Within the first 24 hours after publication, content typically collects 1.39% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 725 views. Within the first day, a publication typically gains 1 053 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 learning, accuracy, distribution, panda, dataset.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โJoin this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free
For collaborations: @love_dataโ
Thanks to the high frequency of updates (latest data received on 14 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.
75 730
Subscribers
+4124 hours
+2197 days
+95430 days
Posts Archive
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Review Fundamental Concepts: Ensure you have a strong grasp of statistics, probability, linear algebra, data structures, algorithms, and programming languages like Python, R, and SQL.
Refresh Machine Learning Knowledge: Familiarize yourself with various machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
Practice Coding: Sharpen your coding skills by solving data science-related problems on platforms like HackerRank, LeetCode, and Kaggle.
Build a Project Portfolio: Showcase your proficiency by creating a portfolio highlighting projects covering data cleaning, wrangling, exploratory data analysis, and machine learning.
Hone Communication Skills: Practice articulating complex technical ideas in simple terms, as effective communication is vital for data scientists when interacting with non-technical stakeholders.
Research the Company: Gain insights into the company's operations, industry, and how they leverage data to solve challenges.
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Bias-variance tradeoff
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Time and space complexity (Big-O notation)
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SELECT, WHERE, GROUP BY, HAVING
JOINS (inner, left, right, full)
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Git and GitHub for version control
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Control vs. treatment group
Hypothesis formulation
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