现已上线！2025 年 Telegram 研究 — 年度关键洞察 
Artificial Intelligence && Deep Learning
前往频道在 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:
显示更多📈 Telegram 频道 Artificial Intelligence && Deep Learning 的分析概览
频道 Artificial Intelligence && Deep Learning (@deeplearning_ai) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 58 029 名订阅者，在 技术与应用 类别中位列第 2 289，并在 印度 地区排名第 6 003 位。
📊 受众指标与增长动态
自 невідомо 创建以来，项目保持高速增长，吸引了 58 029 名订阅者。
根据 24 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -193，过去 24 小时变化为 17，整体触达仍然可观。
- 认证状态： 未认证
- 互动率 (ER)： 平均受众互动率为 9.42%。内容发布后 24 小时内通常能获得 N/A% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 5 467 次浏览，首日通常累积 0 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 16。
- 主题关注点： 内容集中在 github, learning, estimation, dataset, engineer 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台：
“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:”
凭借高频更新（最新数据采集于 25 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。
58 029
订阅者
+1724 小时
-237 天
-19330 天
帖子存档
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
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.
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
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
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
3D Face Reconstruction with Position Map Regression Networks
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
Face Estimation
join👉@DeepLearning_AI
Dataset :- http://domedb.perception.cs.cmu.edu/
Code:- https://github.com/CMU-Perceptual-Computing-Lab/openpose
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
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/
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
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/
Lecture Notes: Regularization for Deep Learning
Join👇👇👇
@DeepLearning_AI
https://towardsdatascience.com/lecture-notes-regularization-be3e7f8e7749
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/
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/
AEI: Artificial ‘Emotional’ Intelligence (source code)
👉@DeepLearning_AI👈
https://towardsdatascience.com/aei-artificial-emotional-intelligence-ea3667d8ece
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
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
