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Data science/ML/AI

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Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

Network:Programming, data science, ML - free courses by Big Data Specialist India28 236 Technologies & Applications9 091...

📈 Analytical overview of Telegram channel Data science/ML/AI

Channel Data science/ML/AI (@datascience_bds) in the English language segment is an active participant. Currently, the community unites 14 058 subscribers, ranking 9 091 in the Technologies & Applications category and 28 236 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 14 058 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 97 over the last 30 days and by -7 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 9.29%. Within the first 24 hours after publication, content typically collects 2.10% reactions from the total number of subscribers.
Post reach: On average, each post receives 1 306 views. Within the first day, a publication typically gains 295 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
Thematic interests: Content is focused on key topics such as panda, learning, row, api, ethic.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...”

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 Technologies & Applications category.

14 058

Subscribers

-724 hours

-17 days

+9730 days

1 306

Post views

~ 29524 hours

~ 42048 hours

9.29%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

14 059

The Simplest Machine Learning Cheatsheet

14 059

📚 Data Science Riddle Two team members run the same notebook but get different results. What's the culprit?

Anonymous voting

14 059

Kafka 101

14 059

A Stanford CS' Lecture note diving into supervised/unsupervised algorithms, neural networks, SVMs with math proofs and Python pseudocode.

14 059

📚 Data Science Riddle A numeric feature has many repeated exact values with occasional jumps. What type of variable is this?

Anonymous voting

14 059

AI vs Machine Learning vs Deep Learning Vs Generative AI

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4 Pillars of Data Science

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📚 Data Science Riddle You fit a forecasting model and residuals show increasing variance. What is needed?

Anonymous voting

14 059

Repost from Programming, data science, ML - free courses by Big Data Specialist

Notes on HDFS, MapReduce, YARN, Hadoop vs. traditional systems and much more... from Columbia University.

14 059

📚 Data Science Riddle Your spark job fails due to executor memory pressure. Most effective optimization?

Anonymous voting

14 059

📚 Data Science Riddle You're working with highly noisy user text. Which tokenization met6handles misspellings best?

Anonymous voting

14 059

Eigenvalues & Eigenvectors — Why PCA Actually Works You’ve heard of PCA. But what’s really happening underneath? PCA finds the directions (vectors) where your data varies the most. Those directions are eigenvectors of the covariance matrix and the eigenvalues tell you how much variance each captures. You’re basically rotating your data to find its “natural axes.”

PCA isn’t compression — it’s discovering how your data wants to be seen.

14 059

📚 Data Science Riddle You're Processing a dataset with frequent schema evolution. Which format handles it most gracefully?

Anonymous voting

14 059

Covariance vs. Correlation: Same Family, Different Story People use them interchangeably but they measure different things. Covariance tells you the direction of relationship (positive or negative). Correlation goes further; it tells you the strength, normalized between -1 and 1. So while covariance can be 2345.67, correlation says 0.92. clear, interpretable, scale-free.

Covariance shows movement, correlation shows consistency.

14 059

K-Means Clustering

14 059

📚 Data Science Riddle A data engineer complains that your model training job is failing in production due to schema mismatch. What's the root fix?

Anonymous voting

14 059

Top 6 Data Concepts

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📚 Data Science Riddle In a real-world NLP project, your model performs poorly on new slang abbreviations. What's the fix?

Anonymous voting

14 059

Covers basics of Linear Regression for modeling numerical data, including assumptions and applications in genetics, from University of Washington.

14 059

Regression Analysis Cheatsheet