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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 Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 819 obunachidan iborat bo'lib, Taʼlim toifasida 2 404-o'rinni va Hindiston mintaqasida 5 049-o'rinni egallagan.

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05 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 77 ga, so‘nggi 24 soatda esa 9 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

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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 Python
Machine Learning with Pythonverified-telegram-icon
67 816
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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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(
        ascii_chars[pixel * (len(ascii_chars) - 1) // 255]
        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
ear error. Key parameters: 🔵Width - determines the size of the final ASCII art 🔵Character palette - affects the detail and style 🔵Aspect ratio - important for correct display 🔵Inversion - you can invert the bright
ness for a dark background Important: ASCII art isn't just a fun thing. It's used to visualize data in the console, create creative logs, and even "hide" information in plain sight. 👩‍💻 @CodeProgrammer

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
🎯 Want to Upskill in IT? Try Our FREE 2026 Learning Kits! SPOTO gives you free, instant access to high-quality, updated reso
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
Most marketers waste HOURS chasing traffic-while their leads slip away! Here’s the blind spot: Speed kills in traffic wars. T
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
Кто я и зачем Я здесь Дмитрий Мачихин, основатель компании BitOK (Бит окей). Предприниматель и инвестор в сфере финансов, web
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Hands On Python Data Science - Data Science Bootcamp Master Python for Data Science with Real-World Applications: Dive Deep i
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
GitHub has launched its learning platform: all #courses and certificates in one place. #Git, #GitHub, #MCP, using #AI, #VSCode, and much more. And most of the content is #free: → https://learn.github.com 👉 @codeprogrammer

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 816
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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𝗧𝗵𝗼𝘀𝗲 𝘄𝗵𝗼 𝘄𝗮𝗻𝘁 𝗿𝗲𝗳𝗲𝗿𝗿𝗮𝗹𝘀 𝗮𝗻𝗱 𝗝𝗼𝗯𝘀 𝗮𝗻𝗱 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽𝘀 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 𝗳𝗿𝗼𝗺 𝗧𝗼𝗽 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗕𝗮𝘀𝗲𝗱, 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗕𝗮𝘀𝗲𝗱 𝗮𝗻𝗱 𝗦𝘁𝗮𝗿𝘁 𝘂𝗽  𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗹𝗶𝗸𝗲 𝗔𝗺𝗮𝘇𝗼𝗻, 𝗚𝗼𝗼𝗴𝗹𝗲,  𝗔𝗽𝗽𝗹𝗲, 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗜𝗕𝗠, 𝗧𝗖𝗦, 𝗖𝗼𝗴𝗻𝗶𝘇𝗮𝗻𝘁, 𝗪𝗶𝗽𝗿𝗼, 𝗖𝗧𝗦, 𝗚𝗼𝗹𝗱𝗺𝗮𝗻 𝗦𝗮𝗰𝗵𝘀, 𝗢𝗹𝗮, 𝗨𝗯𝗲𝗿, 𝗭𝗼𝗺𝗮𝘁𝗼, 𝗦𝘄𝗶𝗴𝗴𝘆, 𝘂𝗽𝗚𝗿𝗮𝗱, 𝗖𝘂𝗿𝗲 𝗙𝗶𝘁, 𝗛𝗮𝗰𝗸𝗲𝗿𝗿𝗮𝗻𝗸, 𝗚𝗲𝗲𝗸𝘀𝗳𝗼𝗿𝗴𝗲𝗲𝗸𝘀 𝗮𝗻𝗱 𝗺𝗮𝗻𝘆 𝗺𝗼𝗿𝗲, 𝗰𝗮𝗻 𝗷𝗼𝗶𝗻 𝘁𝗵𝗲𝘀𝗲 𝗯𝗲𝗹𝗼𝘄 𝗰𝗵𝗮𝗻𝗻𝗲𝗹𝘀 👇👇   https://t.me/jobsandinternshipsupdates

Machine Learning with Python
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💛 Top 10 Best Websites to Learn Machine Learning ⭐️ by [@codeprogrammer] --- 🧠 Google’s ML Course 🔗 https://developers.google.com/machine-learning/crash-course 📈 Kaggle Courses 🔗 https://kaggle.com/learn 🧑‍🎓 Coursera – Andrew Ng’s ML Course 🔗 https://coursera.org/learn/machine-learning ⚡️ Fast.ai 🔗 https://fast.ai 🔧 Scikit-Learn Documentation 🔗 https://scikit-learn.org 📹 TensorFlow Tutorials 🔗 https://tensorflow.org/tutorials 🔥 PyTorch Tutorials 🔗 https://docs.pytorch.org/tutorials/ 🏛️ MIT OpenCourseWare – Machine Learning 🔗 https://ocw.mit.edu/courses/6-867-machine-learning-fall-2006/ ✍️ Towards Data Science (Blog) 🔗 https://towardsdatascience.com --- 💡 Which one are you starting with? Drop a comment below! 👇 #MachineLearning #LearnML #DataScience #AI #TechWithRam

Machine Learning with Python
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