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:

India6 003 Tecnologías y Aplicaciones2 289...

📈 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 58 029 suscriptores, ocupando la posición 2 289 en la categoría Tecnologías y Aplicaciones y el puesto 6 003 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 58 029 suscriptores.

Según los últimos datos del 24 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -193, y en las últimas 24 horas de 17, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 9.42%. 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 5 467 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 25 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.

58 029

Suscriptores

+1724 horas

-237 días

-19330 días

5 467

Visitas de la publicación

Sin datos24 horas

Sin datos48 horas

9.42%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

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Deep Learning for Object Detection: A Comprehensive Review * Single Shot Multibox Detector (SSD) with MobileNets * SSD with Inception V2 * Region-Based Fully Convolutional Networks (R-FCN) with Resnet 101 * Faster RCNN with Resnet 101 * Faster RCNN with Inception Resnet v2 1. join👉@DeepLearning_AI 2.https://towardsdatascience.com/deep-learning-for-object-detection-a-comprehensive-review-73930816d8d9

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Good day dear subscribers. Within this past a year we learn or still learning more about specific topics through channel. I try with my best to provide, keep going with contemporary knowladge and practice, as well as, keep in touch with things based on #AI, #ML, #DL, #DS, #Python. Thanks for being with us and Stay with us.

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CS230 Deep Learning Lectures | Stanford Engineering Deep Learning is one of the most highly sought after skills in AI. In this course, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. 1. join👉@DeepLearning_AI 2. https://www.newworldai.com/cs230-deep-learning-stanford-engineering/?fbclid=IwAR2BXdgS70N5wVeTdnevVL4eF_L3_l67vBetQkCOIoEazDZLeSx5TJUp6t0

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FREE ONLINE COURSES Browse the latest free online courses from HARVARD University including "CS50's Introduction to Game Development", "CS50's Web Programming with Python and JavaScript" , "CS50's Mobile App Development with React Native" and so on.... 1. join👉@DeepLearning_AI 2. https://online-learning.harvard.edu/catalog/free

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3D Face Reconstruction with Position Map Regression Networks 👉 (with source code) 1. join👉@DeepLearning_AI 2. https://heartbeat.fritz.ai/3d-face-reconstruction-with-position-map-regression-networks-36f0ac2d3ef1 3. https://github.com/YadiraF/PRNet

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3D Face Reconstruction with Position Map Regression Networks

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It doesn’t matter if you are beginner or new to machine learning or advanced researcher in the field of deep learning methods and their application, everybody can benefit of Lex Fridman’s course on Deep Learning for Self-Driving Cars. join👉@DeepLearning_AI https://www.newworldai.com/deep-learning-and-self-driving-cars-from-mit-lectures-01-05/?fbclid=IwAR1hxhjsHMihuDNyBvA8zycdPKv6anSkkkpGws3LKsumcdntoVTvQhp8slU

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Face Estimation join👉@DeepLearning_AI Dataset :- http://domedb.perception.cs.cmu.edu/ Code:- https://github.com/CMU-Perceptual-Computing-Lab/openpose

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Real-time and video processing object detection using Tensorflow, OpenCV and Docker. join👉@DeepLearning_AI https://towardsdatascience.com/real-time-and-video-processing-object-detection-using-tensorflow-opencv-and-docker-2be1694726e5

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In today’s brand new tutorial you will learn how to utilize YOLO and Tiny-YOLO for near real-time object detection on the Raspberry Pi with a Movidius NCS (with source code): join👉@DeepLearning_AI https://www.pyimagesearch.com/2020/01/27/yolo-and-tiny-yolo-object-detection-on-the-raspberry-pi-and-movidius-ncs/

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StarGAN v2: Diverse Image Synthesis for Multiple Domains join👉@DeepLearning_AI https://arxiv.org/abs/1912.01865 Un-official TensorFlow Implementation https://github.com/clovaai/stargan-v2

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Intro to anomaly detection with OpenCV, Computer Vision, and scikit-learn 👉(with source code) join👉@DeepLearning_AI https://www.pyimagesearch.com/2020/01/20/intro-to-anomaly-detection-with-opencv-computer-vision-and-scikit-learn/

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Lecture Notes: Regularization for Deep Learning Join👇👇👇 @DeepLearning_AI https://towardsdatascience.com/lecture-notes-regularization-be3e7f8e7749

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Using neural networks to solve advanced mathematics equations Facebook AI has built the first AI system that can solve advanced mathematics equations using symbolic reasoning. By developing a new way to represent complex mathematical expressions as a kind of language and then treating solutions as a translation problem for sequence-to-sequence neural networks. January 14,2020 👉 @DeepLearning_AI👈 https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/

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CS221: Artificial Intelligence: Principles And Techniques | Stanford University What do web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling have in common? These are all complex real-world problems, and the goal of artificial intelligence (AI) is to tackle these with rigorous mathematical tools. 👉@DeepLearning_AI👈 https://www.newworldai.com/cs221-artificial-intelligence-principles-and-techniques-stanford-university/

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AEI: Artificial ‘Emotional’ Intelligence (source code) 👉@DeepLearning_AI👈 https://towardsdatascience.com/aei-artificial-emotional-intelligence-ea3667d8ece

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TensorFlow Lite Now Faster with Mobile GPUs Posted by the TensorFlow team 👉@DeepLearning_AI👈 https://medium.com/tensorflow/tensorflow-lite-now-faster-with-mobile-gpus-developer-preview-e15797e6dee7

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Best of Machine Learning in 2019: Reddit Edition A look at 17 of the most popular projects, research papers, demos, and more from the subreddit r/MachineLearning over the past year 👉@DeepLearning_AI👈 https://heartbeat.fritz.ai/best-of-machine-learning-in-2019-reddit-edition-5fbb676a808