7 Aug 2020, 02:30 UTC≈3,590 viewsread 7 August 2026
⭕️ DeepMind x UCL | Deep Learning Lectures | 1/12 | Intro to Machine Learning & AI https://youtu.be/7R52wiUgxZI 📌via: @cedeeplearning #deepmind #ucl #deeplearning #lecture #AI #machinelearning
Channel
Cutting Edge Deep Learning
@Cedeeplearning
On this record: Topic · Growth · Engagement · Posts · Cite this entry
241subscribers
-4 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 | -1001255142367 |
|---|---|
| Type | Channel |
| Username | @Cedeeplearning |
| Created | Between 1 March 2018 and 6 July 2020 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 8 October 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 2 times, most recently 8 October 2026 |
| On Telegram | t.me/Cedeeplearning |
Topic
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 23 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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 why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 28 Sept 2026, 11:17 | 241 | -1 |
| 6 Sept 2026, 14:22 | 242 | -1 |
| 28 Aug 2026, 11:32 | 243 | -1 |
| 13 Aug 2026, 03:15 | 244 | -1 |
| 7 Aug 2026, 02:31 | 245 | no change |
| 6 Aug 2026, 05:00 | 245 | first reading |
Engagement
20 posts held, back to 6 July 2020 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 7 August 2020. An engagement rate over an empty window would be a number about nothing.
Recent posts
6 Aug 2020, 13:36 UTC≈2,710 viewsread 7 August 2026
File
📕 Building Machine Learning Powered Applications Going from Idea to Product Emmanuel Ameisen 📌@cedeeplearning #book #ML #deeplearning #free #machinelearning
29 Jul 2020, 09:45 UTC≈2,270 viewsread 7 August 2026
Video
⚪️ Basics of Neural Network Programming ✒️ by prof. Andrew Ng 🔹Source: Coursera 🔖 Lecture 27 Why Non-linear Activation Functions Neural Networks and Deep Learning —————————— 📌Via: @cedeeplearning 📌Other social media: https://linktr.ee/cedeeplearning #DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks
29 Jul 2020, 02:45 UTC≈1,950 viewsread 7 August 2026
Photo
⭕️ Neural Manifold Ordinary Differential Equations 📕 Article: https://arxiv.org/abs/2006.10254 🔹 Github: https://github.com/CUVL/Neural-Manifold-Ordinary-Differential-Equations —————— 📌Via: @cedeeplearning
28 Jul 2020, 19:25 UTC≈1,750 viewsread 7 August 2026
⭕️ How You Should Read Research Papers According To Andrew Ng (Stanford Deep Learning Lectures) Instructions on how to approach knowledge acquisition through published research papers by a recognized figure within the world of machine learning and education 🖊 by Richmond Alake link: https://towardsdatascience.com/how-you-should-read-research-papers-according-to-andrew-ng-stanford-deep-learning-lectures-98ecbd3ccfb…
28 Jul 2020, 15:45 UTC≈1,410 viewsread 7 August 2026
Video
⚪️ Basics of Neural Network Programming ✒️ by prof. Andrew Ng 🔹Source: Coursera 🔖 Lecture 26 Activation Functions Neural Networks and Deep Learning —————————— 📌Via: @cedeeplearning 📌Other social media: https://linktr.ee/cedeeplearning #DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks
28 Jul 2020, 13:35 UTC≈1,360 viewsread 7 August 2026
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⭕️ AR-Net: A simple autoregressive NN for Time Series 🔹 blog: https://ai.facebook.com/blog/ar-net-a-simple-autoregressive-neural-network-for-time-series/ 📕 paper: https://arxiv.org/abs/1911.03118 ——————— 📌Via: @cedeeplearning #timeseries #neuralnetworks #machinelearning #deeplearning
28 Jul 2020, 09:15 UTCviews —
Cutting Edge Deep Learning pinned «🔹 Facebook built a powerful AI model to simulate entire social media networks in action ⭕️ When it comes to live-fire high-wire acts in the tech industry, there can be few endeavors more daunting than executing a security update to a software platform hosting…»
28 Jul 2020, 08:35 UTC≈1,190 viewsread 7 August 2026
⭕️ How YOLOv5 solved an ambiguity encountered by YOLOv3 To the ones who not might be knowing, a new version of YOLO (You Only Look Once) is here, namely YOLO v5. Many thanks to Ultralytics for putting this repository together. link: https://towardsdatascience.com/indian-car-license-plate-detection-using-yolo-v5-ae2574578175#4a06-971d24018f84 —————— 📌Via: @cedeeplearning #deeplearning #YOLO #neuralnetworks #selfdri…
27 Jul 2020, 12:35 UTC≈1,070 viewsread 7 August 2026
Video
⚪️ Basics of Neural Network Programming ✒️ by prof. Andrew Ng 🔹Source: Coursera 🔖 Lecture 25 Explanation For Vectorized Implementation Neural Networks and Deep Learning —————————— 📌Via: @cedeeplearning 📌Other social media: https://linktr.ee/cedeeplearning #DeepLearning #machinelearning #AI #coursera #free #python #vectorizing #machinelearning #neuralnetworks
27 Jul 2020, 07:34 UTC983 viewsread 7 August 2026
🔹 Facebook built a powerful AI model to simulate entire social media networks in action ⭕️ When it comes to live-fire high-wire acts in the tech industry, there can be few endeavors more daunting than executing a security update to a software platform hosting more than 2.6 billion users. ⭕️ But that’s exactly what Facebook does every time it rolls out an update. Sure, it mitigates the potential for terror by making…
27 Jul 2020, 02:30 UTC856 viewsread 7 August 2026
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⭕️ Fast and Accurate Neural CRF Constituency Parsing Link on Github: https://github.com/yzhangcs/parser Paper: https://www.ijcai.org/Proceedings/2020/560 ——————— 📌Via: @cedeeplearning #deeplearning #neuralnetworks
Showing the 12 most recent of 20 posts we hold for @Cedeeplearning. 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.
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 28 September 2026 — this entry's latest reading, not the date you are reading this.
“Cutting Edge Deep Learning” (@Cedeeplearning), 241 subscribers as measured 28 September 2026. Telegram Register, tgregister.com/channel/Cedeeplearning.
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.