Telegram RegisterThe public register of Telegram

Channel

Data 2 Pattern

@data_to_pattern

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

112subscribers

+0 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001572590157
TypeChannel
Username@data_to_pattern
DescriptionData science isn't about the quantity of data but rather the quality. — Joo Ann Lee
CreatedBetween 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded9 August 2026
Last confirmed live9 August 2026
Measurements held2
On Telegramt.me/data_to_pattern

Growth

1126 August 2026 — 112 subscribers9 August 2026 — 112 subscribers6 August 20269 August 2026
2 measurements spanning 2 days. 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 111–113 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
9 Aug 2026, 06:33112no change
6 Aug 2026, 23:47112first reading

Engagement

17 posts held, back to 4 October 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
594.2%
avg views ÷ 112 subscribers
Avg views / post
666
2 posts measured
Reaction rate
0.601%
reactions ÷ views · ER floor
Posts in window
2
of 17 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 24 July 2026
Posts held17 (4 October 202524 July 2026)
Views total1,331
Reactions total8
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Aug 2026, 06:33 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
6
Links
27

Lifetime counters from Telegram’s own channel header, read 9 August 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.

Reaction mix

35 reactions across 12 posts, in 5 distinct kinds. The most used accounts for 51.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥1851.4%
514.3%
👍514.3%
👏411.4%
🙏38.57%

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 13 of the 17 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 35reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 17 most recent posts we hold, published 4 October 2025 to 24 July 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.

Recent posts

24 Jul 2026, 17:41 UTC≈1,110 views3 reactionsread 9 August 2026

🚀 Advance Your Career in Quantitative Finance! Applications for the WorldQuant University (WQU) Master of Science in Financial Engineering (MScFE) program are officially open. Whether you're looking to break into quantitative trading, risk management, data science, or financial analytics, this rigorous, practitioner-focused program covers everything from computational finance to advanced modeling. 📋 Admission & Tr

🔥3

18 Jul 2026, 14:30 UTC221 views5 reactionsread 9 August 2026

What I've Been Learning Over the Last Two Days For the past two days, I've been diving into one of the most fascinating topics in backend engineering: how databases physically store and retrieve data. Like many developers, I've spent years writing SQL queries, creating indexes, and building applications on top of databases. But I realized I didn't fully understand what actually happens after executing an INSERT, UP

🔥5

13 Jun 2026, 08:05 UTC137 viewsread 9 August 2026
Forwarded from @ethiopian_ds_ml

guys here is the link you can join live with this link please time 9:00 or 3pm EAT https://www.youtube.com/live/VFj5gV1k6SQ?si=eRnnmF3xuiBD0Wfs and please here is day 1 code link https://www.kaggle.com/code/yisberh/day-1-python-basics please everyone create kaggle.com acount for this course

12 Jun 2026, 17:52 UTC117 viewsread 9 August 2026
Forwarded from @ethiopian_ds_ml

🚀 Free AI Course From Zero — Python to Deep Learning Hello everyone! I am planning to start a free 2-month AI course for beginners. This course will start from basic Python and slowly move into Machine Learning, Deep Learning, Generative AI, and real AI projects. But to begin this class, I need at least 100 serious students. So please, if you are interested, join and also share this message with at least 5 people

4 Jun 2026, 06:47 UTC114 views0 reactionsread 9 August 2026
Forwarded from @ethiopian_ds_ml

Free Beginner Machine Learning Full Course for Ethiopians! 🇪🇹 Hello Ethiopian Data Science & Machine Learning Community, We are excited to announce a complete beginner-friendly Machine Learning course designed for anyone who wants to start learning ML from zero. This course is for you if you are: ✅ New to Machine Learning ✅ Interested in Data Science and AI ✅ A student or self-learner ✅ Looking for practical, step

18 Apr 2026, 14:42 UTC147 views1 reactionsread 9 August 2026
Forwarded from @csec_datascience

ASTU Data Science Bootcamp: Announcement of the Zindi Challenge We are pleased to announce the launch of the ASTU Community Financial Inclusion Hackathon as part of our Data Science Bootcamp. Challenge Details and Registration: https://zindi.africa/competitions/astu-community-financial-inclusion-hackathon Access Code: CSEC_ASTU_COMMUNITY_2018 Start Time: The challenge will officially commence on Tuesday morning a

👍1

17 Apr 2026, 18:37 UTC181 views3 reactionsread 9 August 2026
Photo

FREE DataCamp Premium Scholarship (2026) Want to learn Data Science & AI the right way… for FREE? Through Kumasi Hive × DataCamp, you can get fully sponsored premium access 🎯 What you’ll gain: 🔹 Structured paths → Data Analyst, Data Scientist, ML/AI Engineer 🔹 Hands-on projects with real-world datasets 🔹 Industry-recognized certificates 💡 This is perfect if you’re serious about building real skills (not just watc

🙏3

26 Mar 2026, 04:12 UTC157 viewsread 9 August 2026
Forwarded from @CSEC_ASTUPhoto

🚀Data Science Bootcamp Join our 6-week hands-on bootcamp designed for students who want to go beyond theory and actually build with data. Highlights : • Hands-on learning • Python skills • Real-world challenges 📅 Schedule: 3 days per week ⏳ Deadline: Friday, March 27 at 11:59 PM 🎯 Who should apply? Open for all ASTU students. Second and third-year students are especially encouraged to apply! 🔗 Apply now: LINK F

22 Mar 2026, 14:51 UTC178 viewsread 9 August 2026

🌸 Applications Are Now Open: Women-Only KAIM Cohort 🌸 This is a big moment for women in tech in Ethiopia. The Kifiya AI Mastery Training Program is an intensive 12-week fully online program designed to prepare Ethiopian talent for AI careers in the FinTech sector through hands-on training in Generative AI, Machine Learning, and Data Engineering. And the momentum is real: Our most recent cohort graduated with 52% w

19 Mar 2026, 04:42 UTC125 views1 reactionsread 9 August 2026
Forwarded from @TenAcadPhoto

Call for Builders: Kifiya Inspire 3.0 Hackathon 10 Academy alumni, this one’s for you: build something real, test your skills, and stand out. This is your moment. Join Kifiya Inspire 3.0 and take on the challenge of shaping the future of fintech in Ethiopia by building intelligent, AI-driven infrastructure that can scale. ✔️ The Challenge: Design and build high-scale financial systems powered by AI ✔️ The Opportun

🔥1

31 Dec 2025, 05:26 UTC199 views1 reactionsread 9 August 2026
Forwarded from @ethiopian_ds_ml

📊 Predict SME Financial Health | Zindi Challenge SMEs are vital to Southern Africa’s economy but often financially fragile. Traditional metrics like revenue don’t capture true wellbeing. 🚀 Zindi presents the Financial Health Index (FHI) — a data-driven measure of SME financial stability across savings, debt, resilience, and access to finance. 🤖 Use socio-economic and business data from Eswatini, Lesotho, Zimbabwe

🔥1

27 Oct 2025, 07:26 UTC244 views4 reactionsread 9 August 2026
Forwarded from @CSEC_ASTUPhoto

🎙 Data Science Experience Sharing — Learn from the Best! Curious about how successful data scientists started their journey? 🤔 Join us this Nov 15 as Zindi experts share their inspiring stories, career paths, and lessons learned from real-world data challenges. 💡 Hear firsthand how they navigated obstacles, built winning mindsets, and turned data into impact. Don’t miss this chance to learn, connect, and get inspir

🔥3👍1

Showing the 12 most recent of 17 posts we hold for @data_to_pattern. 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.

Citation-graph rank

Citation-graph rank — 524,643 of 1,183,361entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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

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.

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 August 2026 — this entry's latest reading, not the date you are reading this.

“Data 2 Pattern” (@data_to_pattern), 112 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/data_to_pattern.

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.