Artificial Intelligence && Deep Learning

Open in Telegram

Channel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:

India6 003 Technologies & Applications2 289...

📈 Analytical overview of Telegram channel Artificial Intelligence && Deep Learning

Channel Artificial Intelligence && Deep Learning (@deeplearning_ai) in the English language segment is an active participant. Currently, the community unites 58 029 subscribers, ranking 2 289 in the Technologies & Applications category and 6 003 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 58 029 subscribers.

According to the latest data from 24 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -193 over the last 30 days and by 17 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 9.42%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
Post reach: On average, each post receives 5 467 views. Within the first day, a publication typically gains 0 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 16.
Thematic interests: Content is focused on key topics such as github, learning, estimation, dataset, engineer.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Channel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:”

Thanks to the high frequency of updates (latest data received on 25 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 Technologies & Applications category.

58 029

Subscribers

+1724 hours

-237 days

-19330 days

5 467

Post views

No data24 hours

No data48 hours

9.42%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

58 019

Deep Learning for Object Detection: A Comprehensive Review * Single Shot Multibox Detector (SSD) with MobileNets * SSD with Inception V2 * Region-Based Fully Convolutional Networks (R-FCN) with Resnet 101 * Faster RCNN with Resnet 101 * Faster RCNN with Inception Resnet v2 1. join👉@DeepLearning_AI 2.https://towardsdatascience.com/deep-learning-for-object-detection-a-comprehensive-review-73930816d8d9

58 019

Good day dear subscribers. Within this past a year we learn or still learning more about specific topics through channel. I try with my best to provide, keep going with contemporary knowladge and practice, as well as, keep in touch with things based on #AI, #ML, #DL, #DS, #Python. Thanks for being with us and Stay with us.

58 019

sticker.webp0.16 KB

58 019

CS230 Deep Learning Lectures | Stanford Engineering Deep Learning is one of the most highly sought after skills in AI. In this course, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. 1. join👉@DeepLearning_AI 2. https://www.newworldai.com/cs230-deep-learning-stanford-engineering/?fbclid=IwAR2BXdgS70N5wVeTdnevVL4eF_L3_l67vBetQkCOIoEazDZLeSx5TJUp6t0

58 019

FREE ONLINE COURSES Browse the latest free online courses from HARVARD University including "CS50's Introduction to Game Development", "CS50's Web Programming with Python and JavaScript" , "CS50's Mobile App Development with React Native" and so on.... 1. join👉@DeepLearning_AI 2. https://online-learning.harvard.edu/catalog/free

58 019

3D Face Reconstruction with Position Map Regression Networks 👉 (with source code) 1. join👉@DeepLearning_AI 2. https://heartbeat.fritz.ai/3d-face-reconstruction-with-position-map-regression-networks-36f0ac2d3ef1 3. https://github.com/YadiraF/PRNet

58 019

3D Face Reconstruction with Position Map Regression Networks

58 019

It doesn’t matter if you are beginner or new to machine learning or advanced researcher in the field of deep learning methods and their application, everybody can benefit of Lex Fridman’s course on Deep Learning for Self-Driving Cars. join👉@DeepLearning_AI https://www.newworldai.com/deep-learning-and-self-driving-cars-from-mit-lectures-01-05/?fbclid=IwAR1hxhjsHMihuDNyBvA8zycdPKv6anSkkkpGws3LKsumcdntoVTvQhp8slU

58 019

Face Estimation join👉@DeepLearning_AI Dataset :- http://domedb.perception.cs.cmu.edu/ Code:- https://github.com/CMU-Perceptual-Computing-Lab/openpose

58 019

Real-time and video processing object detection using Tensorflow, OpenCV and Docker. join👉@DeepLearning_AI https://towardsdatascience.com/real-time-and-video-processing-object-detection-using-tensorflow-opencv-and-docker-2be1694726e5

58 019

In today’s brand new tutorial you will learn how to utilize YOLO and Tiny-YOLO for near real-time object detection on the Raspberry Pi with a Movidius NCS (with source code): join👉@DeepLearning_AI https://www.pyimagesearch.com/2020/01/27/yolo-and-tiny-yolo-object-detection-on-the-raspberry-pi-and-movidius-ncs/

58 019

StarGAN v2: Diverse Image Synthesis for Multiple Domains join👉@DeepLearning_AI https://arxiv.org/abs/1912.01865 Un-official TensorFlow Implementation https://github.com/clovaai/stargan-v2

58 019

Intro to anomaly detection with OpenCV, Computer Vision, and scikit-learn 👉(with source code) join👉@DeepLearning_AI https://www.pyimagesearch.com/2020/01/20/intro-to-anomaly-detection-with-opencv-computer-vision-and-scikit-learn/

58 019

Lecture Notes: Regularization for Deep Learning Join👇👇👇 @DeepLearning_AI https://towardsdatascience.com/lecture-notes-regularization-be3e7f8e7749

58 019

Using neural networks to solve advanced mathematics equations Facebook AI has built the first AI system that can solve advanced mathematics equations using symbolic reasoning. By developing a new way to represent complex mathematical expressions as a kind of language and then treating solutions as a translation problem for sequence-to-sequence neural networks. January 14,2020 👉 @DeepLearning_AI👈 https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/

58 019

CS221: Artificial Intelligence: Principles And Techniques | Stanford University What do web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling have in common? These are all complex real-world problems, and the goal of artificial intelligence (AI) is to tackle these with rigorous mathematical tools. 👉@DeepLearning_AI👈 https://www.newworldai.com/cs221-artificial-intelligence-principles-and-techniques-stanford-university/

58 019

AEI: Artificial ‘Emotional’ Intelligence (source code) 👉@DeepLearning_AI👈 https://towardsdatascience.com/aei-artificial-emotional-intelligence-ea3667d8ece

58 019

TensorFlow Lite Now Faster with Mobile GPUs Posted by the TensorFlow team 👉@DeepLearning_AI👈 https://medium.com/tensorflow/tensorflow-lite-now-faster-with-mobile-gpus-developer-preview-e15797e6dee7

58 019

Best of Machine Learning in 2019: Reddit Edition A look at 17 of the most popular projects, research papers, demos, and more from the subreddit r/MachineLearning over the past year 👉@DeepLearning_AI👈 https://heartbeat.fritz.ai/best-of-machine-learning-in-2019-reddit-edition-5fbb676a808