Artificial Intelligence && Deep Learning

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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 With advertising offers contact:

India5 977 Tecnologías y Aplicaciones2 290...

📈 Análisis del canal de Telegram Artificial Intelligence && Deep Learning

El canal Artificial Intelligence && Deep Learning (@deeplearning_ai) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 58 018 suscriptores, ocupando la posición 2 290 en la categoría Tecnologías y Aplicaciones y el puesto 5 977 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 58 018 suscriptores.

Según los últimos datos del 25 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -204, y en las últimas 24 horas de -8, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 9.58%. 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 5 556 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 16.
Intereses temáticos: El contenido se centra en temas clave como github, learning, estimation, dataset, engineer.

📝 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 With advertising offers contact:”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 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

-824 horas

-287 días

-20430 días

5 556

Visitas de la publicación

Sin datos24 horas

Sin datos48 horas

9.58%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

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YOLOv5 is Here: State-of-the-Art Object Detection at 140 FPS # [Tutorial] :https://blog.roboflow.ai/how-to-train-yolov5-on-a-custom-dataset/ # [Video] : https://www.youtube.com/watch?v=MdF6x6ZmLAY&feature=youtu.be #[Repo] : https://github.com/ultralytics/yolov5 #[Colab Notebook] : https://colab.research.google.com/drive/1gDZ2xcTOgR39tGGs-EZ6i3RTs16wmzZQ 1. Join. @DeepLearning_ai https://blog.roboflow.ai/yolov5-is-here/

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YOLOv5 Controversy — Is YOLOv5 Real? 1. @DeepLearning_ai https://medium.com/swlh/yolov5-controversy-is-yolov5-real-20e048bebb08

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DEEP LEARNING WITH PYTORCH Deep Learning with PyTorch provides a detailed, hands-on introduction to building and training neural networks with PyTorch, a popular open source machine learning framework. This full book includes: * Introduction to deep learning and the * PyTorch library * Pre-trained networks * Tensors * The mechanics of learning * Using a neural network to fit data * Using convolutions to generalize * Real-world examples: Building a neural * network designed for cancer detection * Deploying to production 1. Join: @DeepLearning_ai

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Effective Python: 90 Specific Ways to Write Better Python (2nd Edition) (Effective Software Development Series) 1. Join: @DeepLearning_ai

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Real time face recognition with Android + TensorFlow Lite The impressive effect of having the state-of-the-art running on your hands 1. @DeepLearning_ai 2. https://medium.com/@estebanuri/real-time-face-recognition-with-android-tensorflow-lite-14e9c6cc53a5

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The best FREE combined Computer Science curriculum 1. @DeepLearning_ai 2. https://laconicml.com/computer-science-curriculum/

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WELCOME TO PYTORCH TUTORIALS 1. t.me/DeepLearning_ai 2. t.me/ComputerScience_MachineLearning 3 .https://pytorch.org/tutorials/

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1.Join: t.me/DeepLearning_ai 2.Join: t.me/ComputerScience_MachineLearning Paper: https://arxiv.org/pdf/2005.12872.pdf Github (source codes): https://github.com/facebookresearch/detr youtube source: (paper explained): https://www.youtube.com/watch?v=T35ba_VXkMY

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End-to-end object detection with Transformers

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Tesseract OCR: Text localization and detection In this tutorial, you will learn how to utilize Tesseract to detect, localize, and OCR text, all within a single, efficient function call. 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://www.pyimagesearch.com/2020/05/25/tesseract-ocr-text-localization-and-detection/

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Image inpainting with OpenCV and Python 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://www.pyimagesearch.com/2020/05/18/image-inpainting-with-opencv-and-python/

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Deepfakes Series Part1=>Part2=>Part3=>Part4 Finally, our last part of the series looks at detecting Deepfakes videos with machine learning (ML) and/or deep learning (DL). 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://medium.com/@jonathan_hui/deepfakes-series-7138afb825cc

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[CVPR 2020] Learning to See Through Obstructions 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning Paper: https://arxiv.org/abs/2004.01180 Project Page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/ObstructionRemoval Github: https://github.com/alex04072000/ObstructionRemoval

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400+ textbooks free to download CS books on Python, deep learning, data science & AI. You are now only searching within the Free Textbooks and Library Link special issue during Covid 19 package 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning 3. http://bit.ly/SpringerCS

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YOLOv4: Optimal Speed and Accuracy of Object Detection 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning 1. Paper Yolo v4: https://arxiv.org/abs/2004.10934 2. source code: https://github.com/AlexeyAB/darknet

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Springer releases 65 Machine Learning and Data Science books for free 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://techgrabyte.com/springer-released-65-machine-learning-data-science-books-free/?fbclid=IwAR1WhzfMHZenhUaXhYZHdLAn6y5MPJXGycF_qQ7NpGjHYFfAlNhojNR7w6g

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Guide how to learn and master computer vision in 2020 This post will focus on resources, which I believe will boost your knowledge in computer vision the most and mainly based on my own experience. 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://towardsdatascience.com/guide-to-learn-computer-vision-in-2020-36f19d92c934

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Measuring distance between objects in an image with OpenCV 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://www.pyimagesearch.com/2016/04/04/measuring-distance-between-objects-in-an-image-with-opencv/?fbclid=IwAR3DVXClBY0N8Hdv17JdIfCCyo2tdxJp8dRistQdcV7-k_99qzR7IF0AQZE

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The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup. FROM BEGINNERS TO EXPERTS * Source Codes * Videos * Libraries and extensions https://www.tensorflow.org/tutorials

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Pytorch: Step by Step implementation 3D Convolution Neural Network Leran on how to code a PyTorch implementation of 3d CNN 1.Join 👉@DeepLearning_ai 2.Join 👉@ComputerScience_MachineLearning https://towardsdatascience.com/pytorch-step-by-step-implementation-3d-convolution-neural-network-8bf38c70e8b3