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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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Machine Learning with PythonСеть:Machine Learning with PythonИндия4 808Образование2 372

📈 Аналитический обзор Telegram-канала Machine Learning with Python

Канал Machine Learning with Python (@codeprogrammer) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 68 102 подписчиков, занимая 2 372 место в категории Образование и 4 808 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 68 102 подписчиков.

Согласно последним данным от 27 августа, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 112, а за последние 24 часа — 8, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 4.52%. В первые 24 часа после публикации контент обычно набирает 1.90% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 3 077 просмотров. В течение первых суток публикация набирает 1 291 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 5.
  • Тематические интересы: Контент сосредоточен на ключевых темах, таких как insidead, learning, degree, evaluation, algorithm.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Благодаря высокой частоте обновлений (последние данные получены 28 августа, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.

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Machine Learning with Python
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200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
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Repost from Python Courses & Resources
This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

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🧠 Converting images to ASCII: text instead of pixels Want to turn any image into ASCII art? It's not magic, just simple brig
🧠 Converting images to ASCII: text instead of pixels Want to turn any image into ASCII art? It's not magic, just simple brightness processing. It's tedious and stupid to do it manually img = [     [255, 0, 0],     [0, 255, 0] ] # Now we need to pick a symbol for each pixel... # What a hassle. Problem: Manually selecting symbols by brightness is a pain. We need to automate the conversion of grayscale to symbols. ✔️ The right way (using gradation) 
```python
from PIL import Image

def image_to_ascii(path, width=100):
    img = Image.open(path)
    aspect = img.height / img.width
    height = int(width * aspect * 0.55)
    img = img.resize((width, height)).convert('L')

    ascii_chars = '@%#*+=-:. '
    pixels = img.getdata()

    ascii_art = '\n'.join(
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        for pixel in pixels
    )
    lines = [ascii_art[i:i+width] for i in range(0, len(ascii_art), width)]
    return '\n'.join(lines)

print(image_to_ascii('
cat.jpg'))``` How it works: convert('L') converts the image to grayscale Each pixel (0-255) is assigned a symbol from the set The darker the pixel, the "denser" the symbol (e.g., '@'), the lighter - the "weaker" (space) Let's write a converter with customiz
able palette:
```python
class AsciiConverter:
    PALETTES = {
        'default&#39: '@%#*+=-:. ',
        'blocks&#39: '█rayed ',
        'detailed&#39: '$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\\|()1{}[]?-_+~<>i!lI;:,"^`\'. '
    }

    def __init__(self, palette_name='default&#39):
        if palette_name not in self.PALETTES:
            raise ValueError(f'Нет такой палитры, идиот. Выбери из: {list(self.PALETTES.keys())}')
        self.chars = self.PALETTES[palette_name]

    def convert(self, image_path, width=80):
        # ... code to convert using self.chars ...
   
     return ascii_result``` Try specifying a non-existent palette - you'll get a cl
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