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India26 541Educación12 548

📈 Análisis del canal de Telegram DataSpoof

El canal DataSpoof (@dataspoof) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 16 133 suscriptores, ocupando la posición 12 548 en la categoría Educación y el puesto 26 541 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 16 133 suscriptores.

Según los últimos datos del 22 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -144, y en las últimas 24 horas de -5, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.89%. 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 api, llm, pipeline, +9183182, engineer.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn Data Science https://dataspoof4081.graphy.com/membership Artificial Intelligence Machine Learning Data Science Deep learning Computer vision NLP Big data”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 23 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 Educación.

16 133
Suscriptores
-524 horas
-277 días
-14430 días
Archivo de publicaciones
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photo content

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All algorithm related to machinelearning and deep learning
All algorithm related to machinelearning and deep learning

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Today you can learn from the best people in your field at no cost I especially enjoy books written by practitioners: their books are fun to read, useful, and contain no fluff. Here are 3 great ones you can get for free: FastAI deep learning framework by Jeremy Howard https://github.com/fastai/fastbook Approaching almost any machine learning problem ebook Pdf link- https://github.com/abhishekkrthakur/approachingalmost Bayesian method for hackers Pdf link https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

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goldberg_2017_book_draft.pdf

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Unpopular opinion: NLP as a field is moving at a break-neck speed how to get a good hang of it? many asked. While Github Repo
Unpopular opinion: NLP as a field is moving at a break-neck speed how to get a good hang of it? many asked. While Github Repos, MOOCs, videos, papers, datasets, code, and medium posts are good sources, you can't chase millions of them. The trick is to nail the basics down and accelerate your learning speed. It really pays to get your basics right. I recommend this brilliant book. I got all my Neural-NLP basics and advanced lessons from this book, still use it as a reference. (By all means, add other resources, if a particular topic is missing. ). The book is pricey but fortunately, I have a free PDF for you.

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Python for data analysis.pdf12.52 MB

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Github link https://github.com/ParthJadhav/Tkinter-Designer

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Fill the emails who has participated in the giveaway https://forms.gle/vf1mPCChpEXAuD4JA
Fill the emails who has participated in the giveaway https://forms.gle/vf1mPCChpEXAuD4JA

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Giveaway Alert 📢 🚨🚨🚨🚨 Like and comment on this post and follow us on LinkedIn. This is a surprise giveaway and it is distributed when we reach 100+likes. The giveaway will be send on 10th June 2021 https://www.linkedin.com/posts/data-spoof_machinelearning-deeplearning-datascience-activity-6807196663711641600-Fhff

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How AI technologies are being used to better understand retinal diseases AIRA, an artificial intelligence retina analyser, is the result. Being a pattern recognition use case, AI was the obvious solution. PixelPlex was originally given a ‘large array’ of data containing images from fundus cameras, which contained various symptoms and anatomical structures of the human eye, from hemorrhages to arteries and veins. The company added its own data sets from later research, to be used in neural network training. https://artificialintelligence-news.com/2021/05/28/how-ai-technologies-are-being-used-to-better-understand-retinal-diseases/

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CHEATSHEETS for Convolutional neural network.
CHEATSHEETS for Convolutional neural network.

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photo content

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Everyday we tweet about AI news on Twitter

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You can follow us on Twitter to get more news related to ArtificialIntelligence, Data science and other technologies. https://twitter.com/Abhi007si/status/1395698202309922816?s=19

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High level data science roadmaps in 2021 Learn all the skills mention above
High level data science roadmaps in 2021 Learn all the skills mention above