Telegram RegisterThe public register of Telegram
Telegram profile photo for Artificial Intelligence

Channel

Artificial Intelligence

@machinelearning_deeplearning

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry

56,660subscribers

+1,800 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001711296153
TypeChannel
Username@machinelearning_deeplearning
Description🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live9 November 2026
Measurements held64
Confirmed unchanged1 time, most recently 9 November 2026
On Telegramt.me/machinelearning_deeplearning

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 21 August 2026 and assigned it the closest of 31 fixed categories, at 96% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Growth

54,85256,66055,7566 August 20269 November 2026
64 measurements spanning 95 days, net +1,800. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 54,581–56,931 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)SubscribersChange
9 Nov 2026, 18:5056,660+22
8 Nov 2026, 13:4956,638+16
7 Nov 2026, 06:2556,622-5
6 Nov 2026, 05:5756,627+1
5 Nov 2026, 06:5656,626-5
4 Nov 2026, 03:2856,631-2
3 Nov 2026, 03:3856,633+25
2 Nov 2026, 05:4156,608+18
1 Nov 2026, 03:1556,590-8
31 Oct 2026, 03:4056,598+22
30 Oct 2026, 01:3856,576+7
29 Oct 2026, 00:0056,569+16
27 Oct 2026, 20:3756,553+1
26 Oct 2026, 23:1456,552+18
26 Oct 2026, 01:0956,534+3
24 Oct 2026, 22:5056,531+23
23 Oct 2026, 19:1956,508+2
22 Oct 2026, 22:0556,506+15
21 Oct 2026, 20:1156,491+16
20 Oct 2026, 14:4656,475first reading

Engagement

44 posts held, back to 17 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 195 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
4.80%
avg views ÷ 56,660 subscribers
Avg views / post
2,720
9 posts measured
Reaction rate
0.367%
reactions ÷ views · ER floor
Posts in window
9
of 44 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 November 2026
Posts held44 (17 July 2026 – 7 November 2026)
Views total24,500
Reactions total90
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Nov 2026, 23:50 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
488
Videos
5
Links
425

Lifetime counters from Telegram’s own channel header, read 10 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
30s
Average length
30s

Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

622 reactions across 43 posts, in 8 distinct kinds. The most used accounts for 94.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤58794.4%
👏111.77%
👍101.61%
👎50.804%
🥰40.643%
🔥30.482%
🎉10.161%
🙈10.161%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 44 of the 44 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 622 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 44 most recent posts we hold, published 17 July 2026 to 7 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Telegram Stars

Stars received
3
across the posts below
Posts paid on
2
of 44 we hold a reading for · 5%
Most on one post
2
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @machinelearning_deeplearning. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 44 most recent posts we hold for this entry, published 17 July 2026 to 7 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

Telegram’s own ‘edited’ marker: 3 of 9 posts held from the last 30 days (33.3%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

7 Nov 2026, 16:12 UTC≈1,430 views7 reactionsread 10 November 2026

When Should You Use a Tuple? Use a tuple when the collection represents data that should remain fixed. For example: image_size = (1920, 1080) The width and height form a fixed pair of values. Tuples are also commonly used for coordinates: point = (10, 25) 11. Tuples in AI and Data Science Tuples appear frequently in Python-based AI applications. For example, a dataset might contain: sample = ("image_001.jpg…

❤5👍2

7 Nov 2026, 16:12 UTC≈1,140 views7 reactionsread 10 November 2026

In the previous post, we learned about Lists, one of Python's most useful and flexible data structures. Now let's understand another important collection type: Tuples. 📖 Phase 1: Programming Fundamentals 📌 Topic 16: Tuples A Tuple is an ordered collection of items that is immutable, meaning its elements cannot be changed after the tuple is created. Tuples are similar to lists, but the key difference is: • List →…

❤6👍1

5 Nov 2026, 07:15 UTC≈1,620 views15 reactions1 Starread 10 November 2026

In the previous post, we learned about Strings and how Python handles text. Now let's move to another fundamental data structure that you'll use constantly in Python, Data Science, and AI. 📖 Phase 1: Programming Fundamentals 📌 Topic 15: Lists A List is an ordered and mutable collection of items in Python. Lists allow you to store multiple values inside a single variable. For example, instead of creating separate…

❤15

3 Nov 2026, 19:51 UTC≈1,980 views13 reactionsread 10 November 2026

Useful WhatsApp Channels You Should Know ✅ Finance: https://whatsapp.com/channel/0029Vax0HTt7Noa40kNI2B1P Stock Marketing: https://whatsapp.com/channel/0029VatOdpD2f3EPbBlLYW0h Forex: https://whatsapp.com/channel/0029VbDCOLxEgGfH5YZJqs3w Trading: https://whatsapp.com/channel/0029VawmPj05a23woosCRb0d Wealth: https://whatsapp.com/channel/0029Vb8xtRaDOQIfEZtcy41M Financial Accounting: https://whatsapp.com/channel/…

❤11🥰2

1 Nov 2026, 04:42 UTC≈2,740 views10 reactionsread 10 November 2026

🚀 5 Free Courses to Learn AI Engineering 1️⃣ Hugging Face LLM Course 🤗Learn Transf ormers, tokenization, datasets, fine-tuning, and modern LLM workflows. Great for building a strong LLM foundation. 🔗 https://huggingface.co/learn/llm-course 2️⃣ AI Engineer Notebooks 💻Hands-on noteboo ks covering RAG, AI agents, tool calling, evaluations, fine-tuning, LLMOps, and production AI engineering. 🔗 https://github.com/calm…

❤10

22 Oct 2026, 09:31 UTC≈4,590 views0 reactionsread 10 November 2026
Photo

✈️ Flight cancelled. Connection missed. What does your AI agent do? Build the agent that checks flights, reads the policy and recommends the right option. That's one of the capstone projects in the Certification in Agentic AI by Vishlesan i-Hub, IIT Patna. ✅ 4 Months | Online | 10 hrs/week | Live classes ✅ 6+ course projects, 15+ tools ✅ Learn Python, RAG, LangChain, LangGraph & FastAPI ✅ Placement assistance for …

15 Oct 2026, 11:06 UTC≈3,070 views6 reactionsread 10 November 2026

🚀 Welcome back to our AI Engineer Roadmap! ❤️ In the previous post, we learned about Recursion and how a function can call itself to solve smaller versions of a problem. Now let's move to one of the most commonly used data types in Python. 📖 Phase 1: Programming Fundamentals 📌 Topic 14: Strings A String is a sequence of characters used to represent text. Names, sentences, email addresses, file paths, messages, an…

❤6

15 Oct 2026, 11:06 UTC≈5,210 views20 reactions2 Starsread 10 November 2026

word = "Python" word[0] = "J" Instead, you create a new string: word = "Python" word = "J" + word[1:] print(word) # Jython 9. String Concatenation You can combine strings using +. first_name = "Alice" last_name = "Smith" full_name = first_name + " " + last_name print(full_name) # Alice Smith 10. f-Strings f-strings provide a convenient way to insert variables into strings. name = "Alice" age = 25 message = f"…

❤18👏2

15 Oct 2026, 09:02 UTC≈2,720 views12 reactionsread 10 November 2026

🚀 Welcome back to our AI Engineer Roadmap! ❤️ In the previous post, we learned about Lambda Functions and how they can be used with map(), filter(), and sorted(). Now let's move to another important programming concept: Recursion. 📖 Phase 1: Programming Fundamentals 📌 Topic 13: Recursion Recursion is a programming technique in which a function calls itself to solve a problem. Instead of solving the entire proble…

❤12

22 Sept 2026, 10:18 UTC≈6,580 views26 reactionsread 10 November 2026

🚀 Welcome back to our AI Engineer Roadmap! ❤️ In the previous posts, we learned about functions and solved some tricky function-based MCQs. Now let's move to the next topic in Python fundamentals. 📖 Phase 1: Programming Fundamentals 📌 Topic 12: Lambda Functions A Lambda Function is a small, anonymous function that can be written in a single line. Unlike regular functions created using def, lambda functions are c…

❤26

21 Sept 2026, 10:21 UTC≈4,950 views13 reactionsread 10 November 2026

🚀 Welcome back to our AI Engineer Roadmap! ❤️ In the previous post, we explored functions and their significance in programming. Now, let's delve deeper into some advanced concepts related to functions that will further enhance your programming skills. 📖 Phase 1: Programming Fundamentals 📌 Topic 12: Advanced Function Concepts Understanding advanced function concepts will help you write more efficient, readable, a…

❤13

20 Sept 2026, 10:21 UTC≈3,480 views15 reactionsread 10 November 2026

In the previous post, we learned how conditional statements allow Python programs to make decisions. Now let's learn how to repeat tasks efficiently using loops. 📖 Phase 1: Programming Fundamentals 📌 Topic 10: Loops — for and while Loops are used to execute a block of code repeatedly. Imagine you need to print numbers from 1 to 100. Writing print() 100 times would be inefficient. A loop lets you do it with just a…

❤15

Showing the 12 most recent of 44 posts we hold for @machinelearning_deeplearning. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Posts recorded as deleted after publishing

We recorded 1 post on @machinelearning_deeplearning as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.

A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.

First seen missing
15 October 2026
Most recent seen missing
15 October 2026
Median time before seen missing
27 hours
Seen missing in the last 30 days
1

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 14 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

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#4
SQL Programming Resources
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#5
Data Analytics
@sqlspecialist · 110,370
#6
Coding Projects
@Programming_experts · 67,940
#7
Machine Learning
@MachineLearning9 · 41,912
#8
Artificial Intelligence & ChatGPT Prompts
@Curiousprogrammer · 41,965
#9
AI - Artificial Intelligence
@aineeringdotcom · 16,061
#10
AI Prompts | ChatGPT | Google Gemini | Claude
@aiindi · 60,146
#11
Power BI & Tableau Resources
@PowerBI_analyst · 55,653
#12
Python Programming Books
@dsabooks · 59,013
#13
Data Engineers
@sql_engineer · 11,283
#14
Generative AI
@generativeai_gpt · 31,022
#15
Python Projects & Resources
@pythondevelopersindia · 63,326
#16
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@udemy_free_courses_with_certi · 70,309
#17
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#18
Python Courses & Resources
@Python53 · 51,262
#19
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@learndataanalysis · 53,250
#20
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@LearnPython3 · 125,047
#21
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@sqlproject · 39,505
#22
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@webdevcoursefree · 79,292
#23
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@PaperNexus · 34,361
#24
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#25
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#26
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#27
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#28
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@dataanalystinterview · 52,191
#29
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@CodeProgrammer · 68,478
#30
Coding Interview Resources
@crackingthecodinginterview · 51,890
#31
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@machine_learning_courses · 96,444
#32
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@DataScienceInterviews · 27,525
#33
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@deeplearning005 · 11,321
#34
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#35
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#36
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#43
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@datascience_bds · 14,048
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#46
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#47
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@ml_ds_ai_jobs · 25,720
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#53
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@github_repositories_bds · 11,215
#64
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@jobs_SQL · 91,004
#65
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@getjobss · 112,921
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#67
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@excel_analyst · 73,317
#68
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@javascript_courses · 55,621
#69
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@stockmarketinginsights · 25,908
#70
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Finance | Trading Tips | Stock Marketing | Business News
@Finance_Stock_Trading · 23,020
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@BestFinanceBooks · 25,065
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Web Development
@webdev_trainings · 133,578
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Read from Telegram’s recommendation API, most recently 23 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

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Telegram ranks this channel #1 of 65 here — alongside 64 others — read 25 August 2026
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@AI_Best_Tools · 60,007
Telegram ranks this channel #1 of 82 here — alongside 81 others — read 23 August 2026
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Telegram ranks this channel #3 of 87 here — alongside 86 others — read 19 September 2026
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Telegram ranks this channel #3 of 81 here — alongside 80 others — read 29 August 2026
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Telegram ranks this channel #4 of 82 here — alongside 81 others — read 7 September 2026
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@englishlearnerspro · 41,472
Telegram ranks this channel #4 of 80 here — alongside 79 others — read 29 August 2026
Data Science Projects
@pythonspecialist · 56,410
Telegram ranks this channel #4 of 89 here — alongside 88 others — read 23 August 2026
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@aiindi · 60,146
Telegram ranks this channel #4 of 85 here — alongside 84 others — read 23 August 2026
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@udemy_free_courses_with_certi · 70,309
Telegram ranks this channel #4 of 80 here — alongside 79 others — read 20 August 2026
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@Learn_Startup · 33,066
Telegram ranks this channel #5 of 81 here — alongside 80 others — read 4 September 2026
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@FAANGJob · 26,859
Telegram ranks this channel #6 of 76 here — alongside 75 others — read 11 September 2026
Coding & Data Science Resources
@codingfreebooks · 32,483
Telegram ranks this channel #6 of 79 here — alongside 78 others — read 5 September 2026
Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
@sqlproject · 39,505
Telegram ranks this channel #6 of 84 here — alongside 83 others — read 30 August 2026
Power BI & Tableau Resources
@PowerBI_analyst · 55,653
Telegram ranks this channel #6 of 84 here — alongside 83 others — read 23 August 2026
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@AIjobz · 20,921
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CyberSecurity & AI Experts
@EthicalHackingToday · 44,070
Telegram ranks this channel #7 of 67 here — alongside 66 others — read 25 September 2026
Data Science Portfolio - Kaggle Datasets & AI Projects | Artificial Intelligence
@DataPortfolio · 37,776
Telegram ranks this channel #7 of 83 here — alongside 82 others — read 31 August 2026
SQL Programming Resources
@sqlanalyst · 76,328
Telegram ranks this channel #7 of 85 here — alongside 84 others — read 19 August 2026
AI and Machine Learning
@machine_learning_courses · 96,444
Telegram ranks this channel #7 of 74 here — alongside 73 others — read 16 August 2026
LawSikho lawyers' community (2)
@lawyerscommunity2 · 23,951
Telegram ranks this channel #8 of 60 here — alongside 59 others — read 3 October 2026
Digital Marketing Tricks
@digitalmarketing_trick · 22,336
Telegram ranks this channel #8 of 78 here — alongside 77 others — read 21 September 2026

This channel appears in 118 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 9 November 2026 — this entry's latest reading, not the date you are reading this.

“Artificial Intelligence” (@machinelearning_deeplearning), 56,660 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/machinelearning_deeplearning.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.