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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Análisis del canal de Telegram Machine Learning with Python

El canal Machine Learning with Python (@codeprogrammer) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 68 505 suscriptores, ocupando la posición 2 398 en la categoría Educación y el puesto 4 584 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 505 suscriptores.

Según los últimos datos del 30 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 44, y en las últimas 24 horas de -15, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.96%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.47% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 2 712 visualizaciones. En el primer día suele acumular 1 004 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 9.
  • Intereses temáticos: El contenido se centra en temas clave como insidead, learning, degree, evaluation, algorithm.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 31 octubre, 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.

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68 505
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-1524 horas
-1027 días
+4430 días
Archivo de publicaciones
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🤖🧠 Generative AI for Beginners: A Complete Guide to Microsoft’s Free Course 🗓️ 09 Nov 2025 📚 AI News & Trends Generative AI has rapidly shifted from an emerging technology to a foundation of modern digital innovation. From automated writing assistants and AI chatbots to image generators and intelligent search engines, generative AI is transforming industries and shaping the future of work. Whether you are a student, a budding developer or a technology enthusiast, learning generative ... #GenerativeAI #BeginnersGuide #MicrosoftAI #FreeCourse #AIEducation #DigitalInnovation

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🤖🧠 LMCache: Accelerating LLM Inference With Next-Generation KV Cache Technology 🗓️ 08 Nov 2025 📚 AI News & Trends As larg
🤖🧠 LMCache: Accelerating LLM Inference With Next-Generation KV Cache Technology 🗓️ 08 Nov 2025 📚 AI News & Trends As large language models (LLMs) continue to scale in size and complexity, organizations face an increasingly critical challenge: serving models efficiently in real-world applications. While LLM capabilities are rapidly evolving, the bottleneck of inference performance remains a major limitation especially when dealing with long-context workloads or high-traffic enterprise environments. This is where LMCache steps in. ... #LMCache #LLMInference #KVCache #LargeLanguageModels #AIAcceleration #NextGenTechnology

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🤖🧠 Chandra OCR: The Future of Document Understanding and Layout-Aware Text Extraction 🗓️ 08 Nov 2025 📚 AI News & Trends Optical Character Recognition (OCR) has evolved far beyond simply converting scanned text into digital characters. With the rise of artificial intelligence and large language models, the industry is shifting toward intelligent document understanding where structure, context and visual elements matter as much as the text itself. In this landscape, Chandra emerges as a breakthrough solution. ... #ChandraOCR #DocumentUnderstanding #LayoutAwareText #OpticalCharacterRecognition #AIDocumentProcessing #IntelligentOCR

🤖🧠 Pixeltable: The Future of Declarative Data Infrastructure for Multimodal AI Workloads 🗓️ 08 Nov 2025 📚 AI News & Trend
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🤖🧠 Meilisearch: The Lightning-Fast, AI-Ready Search Engine for Modern Applications 🗓️ 08 Nov 2025 📚 AI News & Trends Sear
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🤖🧠 Kimi Linear: The Future of Efficient Attention in Large Language Models 🗓️ 08 Nov 2025 📚 AI News & Trends The rapid ev
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🤖🧠 olmOCR: Redefining Document Understanding with Vision-Language Models 🗓️ 07 Nov 2025 📚 AI News & Trends The digital er
🤖🧠 olmOCR: Redefining Document Understanding with Vision-Language Models 🗓️ 07 Nov 2025 📚 AI News & Trends The digital era has seen an explosion in the amount of information stored in PDFs, scanned documents and image-based files. From research papers and corporate reports to handwritten notes and invoices, these unstructured sources hold trillions of valuable data points. Yet, extracting and converting this data into structured, machine-readable text has long been a challenge. ... #olmOCR #DocumentUnderstanding #VisionLanguageModels #AIInnovation #UnstructuredData #DigitalTransformation

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Core Python Cheatsheet.pdf1.73 KB

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