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 58 018 名订阅者，在 技术与应用 类别中位列第 2 290，并在 印度 地区排名第 5 977 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 58 018 名订阅者。
根据 25 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 -204，过去 24 小时变化为 -8，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 9.58%。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 5 556 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 26 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。
58 018
订阅者
-824 小时
-287 天
-20430 天
帖子存档
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@DeepLearning_AI
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MY FAVORITE FREE COURSES TO LEARN DATA STRUCTURES AND ALGORITHMS IN DEPTH
* Free Courses to Learn Data Structures and Algorithms
* Easy to Advanced Data Structures
* Data Structure Concepts in C
* Algorithms Part 1 - Coursera
* Data Structure in Java
10 Algorithm Books Every Programmer Should Read
10 Books to Prepare Technical Programming/Coding Job Interviews
@DeepLearning_AI
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Gentle Dive into Math Behind Convolutional Neural Networks...
* Autonomous driving, healthcare or retail are just some of the areas where Computer Vision has allowed us to achieve things that, until recently, were considered impossible.
More project ideas to improve your coding skills
an article containing 15 project ideas that you can build to level up your coding skills, and people were very excited about that resource.
Also, the app-ideas repository has gotten almost 3000 stars since I published that article. That’s insane! 😱
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@DeepLearning_AI
@DeepLearning_AI
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YouTube Channel aimed at teaching Machine Learning
Channel link - https://www.youtube.com/BhaveshBhatt8791/
Mastering OpenCV 3 (2nd edition)
Get hands-on with practical Computer Vision using OpenCV 3
This book covers :
Chapter 1, Cartoonifier and Skin Changer for Raspberry Pi
Chapter 2, Exploring Structure from Motion Using OpenCV
Chapter 3, Number Plate Recognition Using SVM and Neural Networks
Chapter 4, Non-Rigid Face Tracking
Chapter 5, 3D Head Pose Estimation Using AAM and POSIT
Chapter 6, Face Recognition Using Eigenfaces or Fisherfaces
Chapter 7, Natural Feature Tracking for Augmented Reality
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@DeepLearning_AI
How to be a great programmer
What sets apart the really great programmers?
5min read...
Three models for Kaggle’s “Flowers Recognition” Dataset (6 min read)
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@DeepLearning_AI
Deep Learning for Cosmetics
In this blog post, how we can use computer vision to solve a particularly poignant instance of this problem: finding influencers, images and videos that address a specific eye shape and complexion. Along the way, we’ll illustrate how three simple yet powerful ideas — geometric transformations, the triplet loss function and transfer learning — allow us to solve a variety of difficult inference problems with minimal human input.
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@DeepLearning_AI
Adversarial Autoencoders on MNIST dataset Python Keras Implementation
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@DeepLearning_AI
This book covers:
Chapter 1, Getting Started with OpenCV.
Chapter 2, An Introduction to the Basics of OpenCV.
Chapter 3, Learning the Graphical User Interface and Basic Filtering.
Chapter 4, Delving into Histograms and Filters.
Chapter 5, Automated Optical Inspection, Object Segmentation, and Detection.
Chapter 6, Learning Object Classification
Chapter 7, Detecting Face Parts and Overlaying Masks,
Chapter 8, Video Surveillance, Background Modeling, and Morphological Operations,
Chapter 9, Learning Object Tracking
Chapter 10, Developing Segmentation Algorithms for Text Recognition,
Chapter 11, Text Recognition with Tesseract
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@DeepLearning_AI
