Computer Science and Programming

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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:

India29 532 Tecnologías y Aplicaciones8 736...

📈 Análisis del canal de Telegram Computer Science and Programming

El canal Computer Science and Programming (@machinelearning_programming) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 14 843 suscriptores, ocupando la posición 8 736 en la categoría Tecnologías y Aplicaciones y el puesto 29 532 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 14 843 suscriptores.

Según los últimos datos del 04 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -152, y en las últimas 24 horas de -7, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 14.63%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 0 visualizaciones. En el primer día suele acumular 0 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
Intereses temáticos: El contenido se centra en temas clave como learning, github, engineer, quantization, detection.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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:”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 05 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

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Suscriptores

-724 horas

-277 días

-15230 días

2 173

Visitas de la publicación

Sin datos24 horas

Sin datos48 horas

14.63%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

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Archivo de publicaciones

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Awesome work ....

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"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

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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-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

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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