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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

Red: Machine Learning with PythonIndia4 586Educación2 406...

📈 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 68 482 suscriptores, ocupando la posición 2 406 en la categoría Educación y el puesto 4 586 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 68 482 suscriptores.

Según los últimos datos del 04 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -75, y en las últimas 24 horas de 7, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.38%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.57% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 2 314 visualizaciones. En el primer día suele acumular 1 073 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 05 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.

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68 482

Suscriptores

+724 horas

-597 días

-7530 días

2 314

Visitas de la publicación

~ 1 07324 horas

~ 1 59648 horas

3.38%

Tasa de compromiso

~ 2

Mensajes por día

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Archivo de publicaciones

68 482

https://t.me/code_stars 5 mins

68 482

How to Download Files From URLs With Python https://realpython.com/python-download-file-from-url https://t.me/CodeProgrammer Please more reaction with our posts

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Code Stars Get ahead of the game with Code Stars! Our platform sends you notifications about the hottest GitHub repositories that are rapidly gaining popularity. Don't miss out - join us now and be the first to discover the trending repositories that everyone will be talking about soon!

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📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide The process of building a stock price prediction model using Python. 1. Import required modules 2. Obtaining historical data on stock prices 3. Selection of features. 4. Definition of features and target variable 5. Preparing data for training 6. Separation of data into training and test sets 7. Building and training the model 8. Making forecasts 9. Trading Strategy Testing https://t.me/CodeProgrammer Please more reaction with our posts

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✋ Hand gesture recognition

import cv2
import mediapipe as mp

# Initialize MediaPipe Hands module
mp_hands = mp.solutions.hands
hands = mp_hands.Hands()

# Initialize MediaPipe Drawing module for drawing landmarks
mp_drawing = mp.solutions.drawing_utils

# Open a video capture object (0 for the default camera)
cap = cv2.VideoCapture(0)

while cap.isOpened():
    ret, frame = cap.read()
    
    if not ret:
        continue
    
    # Convert the frame to RGB format
    frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    
    # Process the frame to detect hands
    results = hands.process(frame_rgb)
    
    # Check if hands are detected
    if results.multi_hand_landmarks:
        for hand_landmarks in results.multi_hand_landmarks:
            # Draw landmarks on the frame
            mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
    
    # Display the frame with hand landmarks
    cv2.imshow('Hand Recognition', frame)
    
    # Exit when 'q' is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the video capture object and close the OpenCV windows
cap.release()
cv2.destroyAllWindows()

68 482

✋ Hand gesture recognition

68 482

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RoadMap: Text Mining (NLP Background) https://t.me/CodeProgrammer

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Data Structures Short Notes ✅

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This channels is for Programmers, Coders, Software Engineers. 0- Python 1- Data Science 2- Machine Learning 3- Data Visualization 4- Artificial Intelligence 5- Data Analysis 6- Statistics 7- Deep Learning 8- programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/DataScienceM

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🔥🖥Roadmap of free courses for learning Python and Machine learning. ▪Data Science ▪ AI/ML ▪ Web Dev 1. Start with this https://kaggle.com/learn/python 2. Take any one of these ❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python ❯ https://scaler.com/topics/course/python-for-beginners/ ❯ https://simplilearn.com/learn-python-basics-free-course-skillup 3. Then take this https://netacad.com/courses/programming/pcap-programming-essentials-python 4. Attempt for this certification https://freecodecamp.org/learn/scientific-computing-with-python/ 5. Take it to next level ❯ Data Scrapping, NumPy, Pandas https://scaler.com/topics/course/python-for-data-science/ ❯ Data Analysis https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis ❯ Data Visualization https://kaggle.com/learn/data-visualization ❯ Django https://openclassrooms.com/courses/6967196-create-a-web-application-with-django ❯ Machine Learning http://developers.google.com/machine-learning/crash-course ❯ Deep Learning (TensorFlow) http://kaggle.com/learn/intro-to-deep-learning

68 482

🔥🖥Roadmap of free courses for learning Python and Machine learning. Roadmap бесплатных курсов для изучения Python и Machine learning. ▪Data Science ▪ AI/ML ▪ Web Dev 📌Курсы с сертификатами. 1. Start with this https://kaggle.com/learn/python 2. Take any one of these ❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python ❯ https://scaler.com/topics/course/python-for-beginners/ ❯ https://simplilearn.com/learn-python-basics-free-course-skillup 3. Then take this https://netacad.com/courses/programming/pcap-programming-essentials-python 4. Attempt for this certification https://freecodecamp.org/learn/scientific-computing-with-python/ 5. Take it to next level ❯ Data Scrapping, NumPy, Pandas https://scaler.com/topics/course/python-for-data-science/ ❯ Data Analysis https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis ❯ Data Visualization https://kaggle.com/learn/data-visualization ❯ Django https://openclassrooms.com/courses/6967196-create-a-web-application-with-django ❯ Machine Learning http://developers.google.com/machine-learning/crash-course ❯ Deep Learning (TensorFlow) http://kaggle.com/learn/intro-to-deep-learning @pythonl

68 482

🖥 Convert PDF to docx using Python ▪Github: https://github.com/dothinking/pdf2docx https://t.me/CodeProgrammer

68 482

👁Savant: Supercharged Computer Vision and Video Analytics Framework on DeepStream

git clone https://github.com/insight-platform/Savant.git
cd Savant/samples/peoplenet_detector
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▪Github: https://github.com/insight-platform/Savant

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