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 14 843 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 14 843 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。

14 843

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

14 843

Awesome work ....

14 843

"A panda is playing guitar on times square" Text2Video-Zero Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators Paper: https://arxiv.org/abs/2303.13439 Video Result: video result link Source code: https://github.com/picsart-ai-research/text2video-zero join us: @MachineLearning_Programming

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MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications. 2023 lectures are starting in just one day, Jan 9th! Link to register: http://introtodeeplearning.com MIT Introduction to Deep Learning The 2022 lectures can be found here: https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI 👉 @deeplearning_ai

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🔥 Machine Learning Operations (MLOps) Specialization Course Demo # FREE CLASS Learn to Design production-ready ML Pipelines to Build, Train and Deploy your Machine learning models on AWS, Azure, GCP & Open- Source tools 📈 Key Highlights of course ✔️ 40 Hours of Live sessions from Industrial Experts ✔️ 50+ Live Hands-on Labs ✔️ 5+ Real-time industrial projects ✔️ One-on-One with Industry Mentors 👉🏻 Registration Link https://bit.ly/mlops-live 🧑🏻‍🎓 What You Will Learn? ▪️Introduction to ML and MLOps stages ▪️Introduction to Git & CI/CD ▪️Docker & Kubernetes Overview ▪️Kubernetes Deployment Strategy ▪️Introduction to Model Management ▪️Feature Store ▪️Cloud ML Services 101 ▪️Kubeflow Intro ▪️Introduction to Model Monitoring ▪️Introduction to Automl tools ▪️Post-Deployment Challenges ☎️ Contact: Sarath Kumar +918940876397 / +918778033930

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Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models Source code: https://github.com/microsoft/visual-chatgpt Paper: https://arxiv.org/pdf/2303.04671v1.pdf @MachineLearning_Programming

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3D-aware Conditional Image Synthesis (pix2pix3D) Pix2pix3D synthesizes 3D objects (neural fields) given a 2D label map, such as a segmentation or edge map Github: https://github.com/dunbar12138/pix2pix3D Paper: https://arxiv.org/abs/2302.08509 Project: https://www.cs.cmu.edu/~pix2pix3D/ Datasets: CelebAMask , AFHQ-Cat-Seg , Shapenet-Car-Edge

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Machine Learning Operations (MLOps) Masterclass 🏆 Unlock your full potential with MLOps Masterclass Learn to Design ML Pipelines to Build, Train,Deploy and Monitor your Machine learning models in a real-time production environment. Register Now👇 https://bit.ly/mlops-class Why you shouldn't miss this Masterclass? ✔️ 15+ hands-on exercises. ✔️ 2 Real-life industry projects. ✔️Dedicated mentoring sessions from industry experts. ✔️ 10 hours session consisting of theory + Hands-on. Schedule: 11th,Sat & 12th,Sun March Highlights of this Masterclass: ▪️Machine Learning Operations (MLOps) Introduction ▪️Getting started with AWS for Machine Learning ▪️AWS SageMaker ▪️CI/CD Tools ▪️AWS MLOps Tools ▪️AWS MLOps - Build, Train & deploy ML Model

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https://youtu.be/yIFCQGBrHls

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GLIGEN: Open-Set Grounded Text-to-Image Generation Project Page: https://gligen.github.io/ Demo: https://dev.hliu.cc/gligen_mirror2/ Paper: https://arxiv.org/abs/2301.07093

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YOLOv8 is the newest state-of-the-art YOLO model that can be used for object detection, image classification, and instance segmentation tasks. YOLOv8 includes numerous architectural and developer experience changes and improvements over YOLOv5. Code: https://github.com/ultralytics/ultralytics What's New in YOLOv8 ? https://blog.roboflow.com/whats-new-in-yolov8/ Yolov8 Instance Segmentation (ONNX): https://github.com/ibaiGorordo/ONNX-YOLOv8-Instance-Segmentation

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Welcome to the Ultralytics YOLOv8 🚀 notebook! YOLOv8 is the latest version of the YOLO object detection and image segmentation model developed by Ultralytics. The YOLOv8 models are designed to be fast, accurate, and easy to use, making them an excellent choice for a wide range of object detection and image segmentation tasks. source code: https://github.com/ultralytics/ultralytics colab : https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb#scrollTo=t6MPjfT5NrKQ MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications. Link to register: http://introtodeeplearning.com MIT Introduction to Deep Learning The 2022 lectures can be found here: https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

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Repost from Artificial Intelligence && Deep Learning

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MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, and applications. 2023 lectures are starting in just one day, Jan 9th! Link to register: http://introtodeeplearning.com MIT Introduction to Deep Learning The 2022 lectures can be found here: https://m.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

14 843

🔥 Machine Learning Operations (MLOps) Specialization Course Demo # FREE CLASS Learn to Design production-ready ML Pipelines to Build, Train and Deploy your Machine learning models on AWS, Azure, GCP & Open- Source tools 📈 Key Highlights of course ✔️ 40 Hours of Live sessions from Industrial Experts ✔️ 50+ Live Hands-on Labs ✔️ 5+ Real-time industrial projects ✔️ One-on-One with Industry Mentors 👉🏻 Registration Link https://bit.ly/mlops-demo-course 🧑🏻‍🎓 What You Will Learn? ▪️Introduction to ML and MLOps stages ▪️Introduction to Git & CI/CD ▪️Docker & Kubernetes Overview ▪️Kubernetes Deployment Strategy ▪️Introduction to Model Management ▪️Feature Store ▪️Cloud ML Services 101 ▪️Kubeflow Intro ▪️Introduction to Model Monitoring ▪️Introduction to Automl tools ▪️Post-Deployment Challenges ☎️ Contact: Sarath Kumar +918940876397 / +918778033930

14 843

Repost from Artificial Intelligence && Deep Learning

Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild Paper: https://arxiv.org/pdf/2207.10660.pdf Github: https://github.com/facebookresearch/omni3d Project page: https://garrickbrazil.com/omni3d/ invite your friends 🌹🌹🌹 @Deeplearning_ai

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The freeCodeCamp community is thrilled to share this new book with you: The Express and Node.js Handbook. This Full Stack JavaScript book will come in handy when you're coding your next web app. You'll learn about JSON API requests, middleware, cookies, routing, static assets, sanitizing, and more. You can read the entire book freely in your browser, and bookmark it for handy reference. Table of Contents How to Install Express The first "Hello, World" example Request Parameters How to Send a Response to the Client How to Send a JSON Response How to Manage Cookies How to Work with HTTP Headers How to Handle Redirects Routing in Express Templates in Express Express Middleware How to Serve Static Assets with Express How to Send Files to the Client Sessions in Express How to Validate Input in Express How to Sanitize Input in Express How to Handle Forms in Express How to Handle File Uploads in Forms in Express https://www.freecodecamp.org/news/the-express-handbook/ invite your friends 🌹🌹🌹 @MachineLearning_Programming

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Deep Face Restoartion: Denoise, Super-Resolution, Deblur and Artifact Removal Table of Contents * Surveys * Deep Blind Face Restoration * Deep Face Super-Resolution * Deep Face Deblurring * Deep Face Denoising * Deep Face Artifact Removal * Other Related Works * Image Quality Assessment * Benchmark Datasets * Recommended Datasets * All Datasets Paper: https://arxiv.org/pdf/2211.02831v1.pdf source code: https://github.com/taowangzj/awesome-face-restoration invite your friends 🌹🌹🌹 @MachineLearning_Programming

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Educational Channels And Videos In YOUTUBE Youtube kanallar contentlari bo'yicha tartiblangan ajoyib web sayt. You may select and enjoy channels regarding on your interests. https://limnology.co/en invite your friends 🌹🌹🌹 @MachineLearning_Programming