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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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تُعد قناة Machine Learning with Python (@codeprogrammer) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 68 117 مشتركاً، محتلاً المرتبة 2 370 في فئة التعليم والمرتبة 4 740 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 68 117 مشتركاً.

بحسب آخر البيانات بتاريخ 29 أغسطس, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 67، وفي آخر 24 ساعة بمقدار 13، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 3.98‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.55‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 2 714 مشاهدة. وخلال اليوم الأول يجمع عادةً 1 053 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 6.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل insidead, learning, degree, evaluation, algorithm.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 30 أغسطس, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

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Core Python Cheatsheet.pdf1.73 KB

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• Apply a simple blur filter.
from PIL import ImageFilter
blurred_img = img.filter(ImageFilter.BLUR)
• Apply a box blur with a given radius.
box_blur = img.filter(ImageFilter.BoxBlur(5))
• Apply a Gaussian blur.
gaussian_blur = img.filter(ImageFilter.GaussianBlur(radius=2))
• Sharpen the image.
sharpened = img.filter(ImageFilter.SHARPEN)
• Find edges.
edges = img.filter(ImageFilter.FIND_EDGES)
• Enhance edges.
edge_enhanced = img.filter(ImageFilter.EDGE_ENHANCE)
• Emboss the image.
embossed = img.filter(ImageFilter.EMBOSS)
• Find contours.
contours = img.filter(ImageFilter.CONTOUR)
VII. Image Enhancement (ImageEnhance) • Adjust color saturation.
from PIL import ImageEnhance
enhancer = ImageEnhance.Color(img)
vibrant_img = enhancer.enhance(2.0)
• Adjust brightness.
enhancer = ImageEnhance.Brightness(img)
bright_img = enhancer.enhance(1.5)
• Adjust contrast.
enhancer = ImageEnhance.Contrast(img)
contrast_img = enhancer.enhance(1.5)
• Adjust sharpness.
enhancer = ImageEnhance.Sharpness(img)
sharp_img = enhancer.enhance(2.0)
VIII. Drawing (ImageDraw & ImageFont) • Draw text on an image.
from PIL import ImageDraw, ImageFont
draw = ImageDraw.Draw(img)
font = ImageFont.truetype("arial.ttf", 36)
draw.text((10, 10), "Hello", font=font, fill="red")
• Draw a line.
draw.line((0, 0, 100, 200), fill="blue", width=3)
• Draw a rectangle (outline).
draw.rectangle([10, 10, 90, 60], outline="green", width=2)
• Draw a filled ellipse.
draw.ellipse([100, 100, 180, 150], fill="yellow")
• Draw a polygon.
draw.polygon([(10,10), (20,50), (60,10)], fill="purple")
#Python #Pillow #ImageProcessing #PIL #CheatSheet ━━━━━━━━━━━━━━━ By: @CodeProgrammer

💡 Top 50 Pillow Operations for Image Processing I. File & Basic Operations • Open an image file.
from PIL import Image
img = Image.open("image.jpg")
• Save an image.
img.save("new_image.png")
• Display an image (opens in default viewer).
img.show()
• Create a new blank image.
new_img = Image.new("RGB", (200, 100), "blue")
• Get image format (e.g., 'JPEG').
print(img.format)
• Get image dimensions as a (width, height) tuple.
width, height = img.size
• Get pixel format (e.g., 'RGB', 'L' for grayscale).
print(img.mode)
• Convert image mode.
grayscale_img = img.convert("L")
• Get a pixel's color value at (x, y).
r, g, b = img.getpixel((10, 20))
• Set a pixel's color value at (x, y).
img.putpixel((10, 20), (255, 0, 0))
II. Cropping, Resizing & Pasting • Crop a rectangular region.
box = (100, 100, 400, 400)
cropped_img = img.crop(box)
• Resize an image to an exact size.
resized_img = img.resize((200, 200))
• Create a thumbnail (maintains aspect ratio).
img.thumbnail((128, 128))
• Paste one image onto another.
img.paste(another_img, (50, 50))
III. Rotation & Transformation • Rotate an image (counter-clockwise).
rotated_img = img.rotate(45, expand=True)
• Flip an image horizontally.
flipped_img = img.transpose(Image.FLIP_LEFT_RIGHT)
• Flip an image vertically.
flipped_img = img.transpose(Image.FLIP_TOP_BOTTOM)
• Rotate by 90, 180, or 270 degrees.
img_90 = img.transpose(Image.ROTATE_90)
• Apply an affine transformation.
transformed = img.transform(img.size, Image.AFFINE, (1, 0.5, 0, 0, 1, 0))
IV. ImageOps Module Helpers • Invert image colors.
from PIL import ImageOps
inverted_img = ImageOps.invert(img)
• Flip an image horizontally (mirror).
mirrored_img = ImageOps.mirror(img)
• Flip an image vertically.
flipped_v_img = ImageOps.flip(img)
• Convert to grayscale.
grayscale = ImageOps.grayscale(img)
• Colorize a grayscale image.
colorized = ImageOps.colorize(grayscale, black="blue", white="yellow")
• Reduce the number of bits for each color channel.
posterized = ImageOps.posterize(img, 4)
• Auto-adjust image contrast.
adjusted_img = ImageOps.autocontrast(img)
• Equalize the image histogram.
equalized_img = ImageOps.equalize(img)
• Add a border to an image.
bordered = ImageOps.expand(img, border=10, fill='black')
V. Color & Pixel Operations • Split image into individual bands (e.g., R, G, B).
r, g, b = img.split()
• Merge bands back into an image.
merged_img = Image.merge("RGB", (r, g, b))
• Apply a function to each pixel.
brighter_img = img.point(lambda i: i * 1.2)
• Get a list of colors used in the image.
colors = img.getcolors(maxcolors=256)
• Blend two images with alpha compositing.
# Both images must be in RGBA mode
blended = Image.alpha_composite(img1_rgba, img2_rgba)
VI. Filters (ImageFilter)