Machine Learning
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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
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Red:📈 Análisis del canal de Telegram Machine Learning
El canal Machine Learning (@machinelearning9) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 310 suscriptores, ocupando la posición 3 332 en la categoría Tecnologías y Aplicaciones y el puesto 225 en la región Siria.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 310 suscriptores.
Según los últimos datos del 09 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 378, y en las últimas 24 horas de 30, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.23%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.95% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 897 visualizaciones. En el primer día suele acumular 788 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
- Intereses temáticos: El contenido se centra en temas clave como distance, insidead, gpu, learning, degree.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 10 julio, 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.
40 310
Suscriptores
+3024 horas
+1067 días
+37830 días
Archivo de publicaciones
40 310
📌 The Gamma Hurdle Distribution
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-07 | ⏱️ Read time: 11 min read
Which Outcome Matters? Here is a common scenario : An A/B test was conducted, where…
40 310
📌 Six Ways to Control Style and Content in Diffusion Models
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-10 | ⏱️ Read time: 9 min read
Stable Diffusion 1.5/2.0/2.1/XL 1.0, DALL-E, Imagen… In the past years, diffusion models have showcased stunning…
40 310
📌 Polars vs. Pandas — An Independent Speed Comparison
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-02-11 | ⏱️ Read time: 13 min read
Overview Introduction — Purpose and Reasons Speed is important when dealing with large amounts of…
40 310
📌 Data vs. Business Strategy
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-11 | ⏱️ Read time: 12 min read
There seems to be a consensus that leveraging data, analytics, and AI to create a…
40 310
📌 Understanding Model Calibration: A Gentle Introduction & Visual Exploration
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-11 | ⏱️ Read time: 16 min read
How Reliable Are Your Predictions? About To be considered reliable, a model must be calibrated…
40 310
📌 4-Dimensional Data Visualization: Time in Bubble Charts
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-11 | ⏱️ Read time: 9 min read
Bubble charts elegantly compress large amounts of information into a single visualization, with bubble size…
40 310
📌 Virtualization & Containers for Data Science Newbies
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-11 | ⏱️ Read time: 12 min read
Virtualization makes it possible to run multiple virtual machines (VMs) on a single piece of…
40 310
📌 Build a Decision Tree in Polars from Scratch
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-12 | ⏱️ Read time: 21 min read
Decision tree algorithms have always fascinated me. They are easy to implement and achieve good…
40 310
📌 Branching Out: 4 Git Workflows for Collaborating on ML
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-12 | ⏱️ Read time: 11 min read
It’s been more than 15 years since I finished my master’s degree, but I’m still…
40 310
📌 Pandas Can’t Handle This: How ArcticDB Powers Massive Datasets
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-12 | ⏱️ Read time: 14 min read
Python has grown to dominate data science, and its package Pandas has become the go-to…
40 310
📌 Manage Environment Variables with Pydantic
🗂 Category: PROGRAMMING
🕒 Date: 2025-02-12 | ⏱️ Read time: 5 min read
Introduction Developers work on applications that are supposed to be deployed on some server in…
40 310
📌 Method of Moments Estimation with Python Code
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-12 | ⏱️ Read time: 10 min read
Let’s say you are in a customer care center, and you would like to know…
40 310
📌 Should Data Scientists Care About Quantum Computing?
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-12 | ⏱️ Read time: 6 min read
I am sure the quantum hype has reached every person in tech (and outside it,…
40 310
📌 Learnings from a Machine Learning Engineer — Part 2: The Data Sets
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-13 | ⏱️ Read time: 10 min read
In Part 1, we discussed the importance of collecting good image data and assigning proper labels…
40 310
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40 310
🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the hottest skill in tech: building intelligent AI systems that think and act independently.
Learn to build smart 𝗰𝗵𝗮𝘁𝗯𝗼𝘁𝘀, 𝗔𝗜 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀 𝗮𝗻𝗱 𝗺𝘂𝗹𝘁𝗶-𝗮𝗴𝗲𝗻𝘁 𝘀𝘆𝘀𝘁𝗲𝗺𝘀.
𝗘𝗮𝗿𝗻 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 and 𝗴𝗲𝘁 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝗯𝘆 𝘁𝗼𝗽 𝗔𝗜 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗿𝘀.
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40 310
📌 Data Roles, Small Language Models, Knowledge Graphs, and More: Our January Must-Reads
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-30 | ⏱️ Read time: 5 min read
The stories that resonated the most with our community in the past month
40 310
📌 Time Series Forecasting with MFLES
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-01-30 | ⏱️ Read time: 7 min read
The newest method in StatsForecast
40 310
📌 Nine Pico PIO Wats with Rust (Part 1)
🗂 Category: PROGRAMMING
🕒 Date: 2025-01-30 | ⏱️ Read time: 19 min read
Raspberry Pi programmable IO pitfalls illustrated with a musical example
