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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Red:📈 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 68 536 suscriptores, ocupando la posición 2 402 en la categoría Educación y el puesto 4 600 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 536 suscriptores.
Según los últimos datos del 29 octubre, 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 -5, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.84%. 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 2 629 visualizaciones. En el primer día suele acumular 1 007 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 30 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.
68 536
Suscriptores
-524 horas
-847 días
+7430 días
Archivo de publicaciones
For those interested in joining our Premium channel, which contains over 5,000 books and 200 courses in machine learning, programming languages, data analysis, LLM, and other related fields with daily updates>
We offer a 15-minute free trial to explore the channel's content. Afterward, you can subscribe to the channel for $50 – a permanent subscription.
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t.me/HusseinSheikho
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How to test code without a real database
During unit testing, connecting to a real DB is unnecessary: • tests run slowly • become unstable • require a working serverIt is much better to mock the call to
pandas.read_sql and return dummy data
Example function:
def query_user_data(user_id):
query = f"SELECT id, name FROM users WHERE id = {user_id}"
return pd.read_sql(query, "postgresql://localhost/mydb")from unittest.mock import patch
import pandas as pd
@patch("pandas.read_sql")
def test_database_query_mocked(mock_read_sql):
mock_read_sql.return_value = pd.DataFrame(
{"id": [123], "name": ["Alice"]}
)
result = query_user_data(user_id=123)
assert result["name"].iloc[0] == "Alice"
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Repost from Learn Python Coding
Checking the reliability of a password with Python!
Sometimes you need to quickly check how secure a password is. Let's look at a simple example using regular expressions - a good opportunity to practice with
re and conditional logic.
Import the module:
import redef check_password_strength(password):
length = len(password) >= 8
upper = re.search(r"[A-Z]", password)
lower = re.search(r"[a-z]", password)
digit = re.search(r"\d", password)
special = re.search(r"[@$!%*?&]", password)
if all([length, upper, lower, digit, special]):
return "✅ Reliable password"
else:
return "⚠️ Weak password"print(check_password_strength("Qwerty123"))
print(check_password_strength("Qw!8zYt@1"))⚠️ Weak password
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Repost from Github Top Repositories
Create a perfect resume without messing with templates.
You write content in YAML and generate a PDF.
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Admin: @HusseinSheikho
