Computer Science and Programming

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 * Related Courses and Ebooks With advertising offers contact:

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印度29 532 技术与应用8 736...

📈 Telegram 频道 Computer Science and Programming 的分析概览

频道 Computer Science and Programming (@machinelearning_programming) 英语语言赛道中的是活跃参与者。目前社区聚集了 14 846 名订阅者，在 技术与应用 类别中位列第 8 736，并在印度地区排名第 29 532 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 14 846 名订阅者。

根据 04 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 -152，过去 24 小时变化为 -7，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 14.63%。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 0 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 0。
主题关注点： 内容集中在 learning, github, engineer, quantization, detection 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 * Related Courses and Ebooks With advertising offers contact:”

凭借高频更新（最新数据采集于 05 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。

14 846

订阅者

-724 小时

-277 天

-15230 天

2 173

帖子浏览量

无数据24 小时

无数据48 小时

14.63%

参与率

无数据

每日帖子数

Ads index

beta

帖子存档

14 846

Course Catalog Download All Udemy Paid Courses And Tutorials FREE - Course Catalog Why Course Catalog? - Course Catalog - Upload New Tutorials And Courses On CourseCatalog.us Every Day. So If You Want To Download More Free Courses And Free Tutorials Then Visit them, Again And Again, to get paid courses for free. Free Tutorials: - The Course Catalog is the largest and most famous website in the world, providing free tutorials on all areas of computer science. Coursecatalog - From Coursecatalog You can find solutions for your IT problems. You can easily find thousands of video tutorials provided by experts here. The coursecatalog contains many free tutorials. t.me/deeplearning_ai 👇👇👇

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A curated list of awesome Python frameworks, libraries, software and resources. github: https://github.com/vinta/awesome-python https://t.me/MachineLearning_Programming

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Millions of learners have used Class Central to find their next course. https://www.classcentral.com/ Join us and stay up to date with the latest news, research papers with spurce codes, books related to AI/ML/DL

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Millions of learners have used Class Central to find their next course. JOIN US AND STAY UP TO DATE WITH LATEST RESEARCH PAPERS with SOURCE CODE related to Artificial Intelligence https://www.classcentral.com/

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Github: https://github.com/OlafenwaMoses/DeepStack_ExDark Documentation: https://docs.deepstack.cc/index.html#installation Custom dataset preparation: https://docs.deepstack.cc/custom-models/datasetprep/index.html Training custom model: https://docs.deepstack.cc/custom-models/training/index.html

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Dark scene object detection API for detecting 12 common objects in the dark/night images and videos

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500 + 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲 https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 👉https://t.me/MachineLearning_Programming

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3 Tools to Track and Visualize the Execution of your Python Code https://towardsdatascience.com/3-tools-to-track-and-visualize-the-execution-of-your-python-code-666a153e435e 👉https://t.me/MachineLearning_Programming

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Find and remove duplicate images in your dataset Improve your deep learning image datasets by automatically detecting duplicate and near-duplicate images and removing them https://towardsdatascience.com/find-and-remove-duplicate-images-in-your-dataset-3e3ec818b978 https://t.me/MachineLearning_Programming

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ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation [Cited by 452] paper: http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17tits.pdf github [PyTorch]: https://github.com/Eromera/erfnet_pytorch

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Graph Neural Networks (GNN, GAE, STGNN) https://jonathan-hui.medium.com/graph-neural-networks-gnn-gae-stgnn-1ac0b5c99550 https://t.me/MachineLearning_Programming

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http://introtodeeplearning.com/

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MIT 6.S191 Introduction to Deep Learning 2021 Course Description MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. Listeners are welcome!

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The Top 1,157 Computer Vision Open Source Projects https://awesomeopensource.com/projects/computer-vision https://t.me/MachineLearning_Programming

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21 Python Mini Projects With Code https://levelup.gitconnected.com/21-python-mini-projects-with-codes-c4126e4131e4 https://t.me/MachineLearning_Programming

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Project Page: https://github.com/TZYSJTU/Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale Paper: https://arxiv.org/pdf/2012.09004.pdf https://t.me/MachineLearning_Programming

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sticker.webp0.15 KB

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Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net https://deepai.org/publication/fast-and-furious-real-time-end-to-end-3d-detection-tracking-and-motion-forecasting-with-a-single-convolutional-net Join: https://t.me/DeepLearning_ai