Computer Science and Programming

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Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_science

Red:Computer Science and Programming Italia88 Tecnologías y Aplicaciones811...

📈 Análisis del canal de Telegram Computer Science and Programming

El canal Computer Science and Programming (@computer_science_and_programming) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 140 416 suscriptores, ocupando la posición 811 en la categoría Tecnologías y Aplicaciones y el puesto 88 en la región Italia.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 140 416 suscriptores.

Según los últimos datos del 01 septiembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -772, y en las últimas 24 horas de -64, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 8.15%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.97% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 11 442 visualizaciones. En el primer día suele acumular 2 771 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 13.
Intereses temáticos: El contenido se centra en temas clave como sellerflash, github, developer, pricing, waybienad.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_sc...”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 02 septiembre, 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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140 416

Suscriptores

-6424 horas

-2617 días

-77230 días

11 442

Visitas de la publicación

~ 2 77124 horas

~ 3 80448 horas

8.15%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

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Archivo de publicaciones

140 416

Differential Machine Learning

140 416

FREE PDF download: https://d2l.ai/d2l-en.pdf Download the book in 'notebook' format to read and execute locally: https://d2l.ai/chapter_installation/index.html Website: https://d2l.ai Github: https://github.com/d2l-ai/d2l-en Article: https://www.amazon.science/latest-news/amazon-scientists-author-popular-deep-learning-book

140 416

Dive Into Deep Learning August 2020 and FREE version!!! D2L is the 987-page book that Amazon scientists have compiled over the past two years and has finally been completed... an interactive and ' open source book ' with code, math and discussions. What makes this book unique is that it was created with Jupyter Notebook and with the idea of ′′ Learning with Practice "... that is, the book in its entirety consists of executable code with adaptations in PyTorch, TensorFlow and MXNet.

140 416

Classification library https://github.com/Tessellate-Imaging/monk_v1 Notebooks - https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/4_image_classification_zoo Detection and Segmentation Library https://github.com/Tessellate-Imaging/ Monk_Object_Detection Notebooks: https://github.com/Tessellate-Imaging/Monk_Object_Detection/tree/master/application_model_zoo

140 416

80+ Jupyter Notebook tutorials on image classification, object detection and image segmentation in various domains 📌 Agriculture and Food 📌 Medical and Healthcare 📌 Satellite 📌 Security and Surveillance 📌 ADAS and Self Driving Cars 📌 Retail and E-Commerce 📌 Wildlife

140 416

Blog: https://towardsdatascience.com/pp-yolo-surpasses-yolov4-object-detection-advances-1efc2692aa62 Github: https://github.com/PaddlePaddle/PaddleDetection

140 416

Baidu publishes PP-YOLO and pushes the state of the art in object detection research.

140 416

Tackled the problem of defining a perturbation set for real-world perturbations which cannot be easily described with a set of equations. Paper: https://arxiv.org/abs/2007.08450 Blog post: https://locuslab.github.io/2020-07-20-perturbation/ Code: https://github.com/locuslab/perturbation_learning

140 416

Learning perturbation sets for robust machine learning

140 416

https://laconicml.com/

140 416

One more great source of Data Science, Deep Learning, Machine Learning, Computer Vision, AI and more... Enjoy with hot topics and projects

140 416

https://github.com/rasbt/deeplearning-models

140 416

Up-to-date and detailed explanation of Deep Learning Models from Sebastian Raschka A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks. (80 Jupyter Notebook notes in total)

140 416

https://arxiv.org/pdf/2003.11755.pdf

140 416

Recently published Comprehensive survey about role of Deep Learning for Scientific discovery (March, 2020). Well structured information given from the authors by providing supplementary materials (Github code links). It worth to spend time to read.

140 416

https://aihub.org/

140 416

One more great website specialized to AI with News, Articles, Opinions, Tutorials, Resources and much more supported by Geeks of AI

140 416

https://laconicml.com/free-artificial-intelligence-courses/?fbclid=IwAR2oQoGYdTqiQ6sOJC7LvJxpaeSVVBLwk6Fs7S-_p2iMDq-BqbrpqBUqUrc

140 416

List some of the free Artificial Intelligence courses that come from Harvard University, MIT University, and Stanford University that anyone can attend, no matter where you live

140 416

But, You can follow what happens there almost in real time: fill below link and receive every day during CVPR the official magazine CVPR Daily (16-17-18 June) - with all the highlights from CVPR, the Computer Vision and Pattern Recognition conference. https://www.rsipvision.com/feel-at-cvpr-as-if-you-were-at-cvpr/ Open Access version of papers are available at: http://openaccess.thecvf.com/CVPR2020.py