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 68 475 suscriptores, ocupando la posición 2 403 en la categoría Educación y el puesto 4 579 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 475 suscriptores.
Según los últimos datos del 03 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -74, y en las últimas 24 horas de 12, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 4.07%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.55% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 789 visualizaciones. En el primer día suele acumular 1 062 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 8.
- 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 04 noviembre, 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.
68 475
Suscriptores
+1224 horas
-827 días
-7430 días
Archivo de publicaciones
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Hey guys,
As you all know, the purpose of this community is to share notes and grow together. Hence, today I am sharing with you an app called DevBytes. It keeps you updated about dev and tech news.
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It’s time to read less and know more!
Hey guys,
As you all know, the purpose of this community is to share notes and grow together. Hence, today I am sharing with you an app called DevBytes. It keeps you updated about dev and tech news.
This brilliant app provides curated, bite-sized updates on the latest tech news/dev content. Whether it’s new frameworks, AI breakthroughs, or cloud services, DevBytes brings the essentials straight to you.
If you're tired of information overload and want a smarter way to stay informed, give DevBytes a try.
Download here: https://play.google.com/store/apps/details?id=com.candelalabs.devbytes&hl=en-IN
It’s time to read less and know more!
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Pandas 🐼 to Polars Guide
🔑 Tags: #PYTHON #AI #ML #pandas #Polars
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🏳️🌈 Python became GitHub's first language!
👨🏻💻 In a recent GitHub report, with the expansion of artificial intelligence, Python could finally overtake JavaScript and become the most popular language on GitHub in 2024. This happened after 10 years of JavaScript dominance and it is not very strange.
✔️ Because with the growth of artificial intelligence, developers are turning to Python more than ever, and Python's applications in data science and analytics are increasing every day. You can read the full GitHub report here:👇
┌ 🐱 Top programming along GitHub
├ 💰 Report
⏪ I also introduced the most important Python libraries for working with data and AI here: 👇
🖥 Data Manipulation & Analysis
▶️ pandas
▶️ Apache Spark
▶️ Polars
▶️ DuckDB
📊 Data Visualization
➡️ matplotlib
➡️ plotly
➡️ seaborn
🖥 Machine & Deep Learning
➡️ TensorFlow
➡️ PyTorch
➡️ Keras
➡️ scikit-learn
➡️ XGBoost
➡️ LightGBM
➡️ Prophet
🌫 NLP & Large Language Models
➡️ Hugging Face Transformers
➡️ LangChain
➡️ LlamaIndex
🔑 Tags: #PYTHON #AI #ML #NLP
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Confusion matrix (TP, FP, TN, FN), clearly explained
🔑 Tags: #PYTHON #AI #ML
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Convert PDF to docx using Python
📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses
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Coursera has launched a collaboration with the MAJOR platform to enable students to self-fund using the MAJOR platform.
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A Popular Interview Question: Discriminative vs. Generative Models
More Details: https://blog.dailydoseofds.com/p/a-popular-interview-question-discriminative
📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses
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How LLMs work, clearly explained ⭐
📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses
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