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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📈 Analytical overview of Telegram channel Machine Learning with Python
Channel Machine Learning with Python (@codeprogrammer) in the English language segment is an active participant. Currently, the community unites 68 482 subscribers, ranking 2 406 in the Education category and 4 586 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 482 subscribers.
According to the latest data from 04 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -75 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.38%. Within the first 24 hours after publication, content typically collects 1.57% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 314 views. Within the first day, a publication typically gains 1 073 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
- Thematic interests: Content is focused on key topics such as insidead, learning, degree, evaluation, algorithm.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Thanks to the high frequency of updates (latest data received on 05 November, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
68 482
Subscribers
+724 hours
-597 days
-7530 days
Posts Archive
import PyPDF2
import pyttsx3
# Read the pdf by specifying the path in your computer
pdfReader = PyPDF2.PdfFileReader(open('clcoding.pdf', 'rb'))
# Get the handle to speaker
speaker = pyttsx3.init()
# split the pages and read one by one
for page_num in range(pdfReader.numPages):
text = pdfReader.getPage(page_num).extractText()
speaker.say(text)
speaker.runAndWait()
# stop the speaker after completion
speaker.stop()
# save the audiobook at specified path
engine.save_to_file(text, 'E:\audio.mp3')
engine.runAndWait()![🌴Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023] 🌴 Learn to create Machine Learning Algorithms in Python and R](https://cdn.tlmtr.io/_next/static/media/empty-channel.35ed232f.svg)
🌴Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023] 🌴
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
This course includes:
42 hours on-demand video
5 coding exercises
39 articles
9 downloadable resources
🟢 Price :- $20
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Contact @hussein_sheikho
🖥 Face swap on python.
pip install --user opencv-python insightface matplotlib
# скачай 'inswapper_128.onnx' отсюда 'clck.ru/36ct6v' и закинь в папку с кодом
import cv2
import insightface
from insightface.app import FaceAnalysis
import matplotlib.pyplot as plt
app = FaceAnalysis(name='buffalo_l')
app.prepare(ctx_id=0, det_size=(640, 640))
swapper = insightface.model_zoo.get_model('inswapper_128.onnx')
def swap_faces(img):
img = cv2.imread(img)
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
ax.imshow(img[:,:,::-1])
ax.axis('off'); plt.show()
faces = app.get(img)
face1, face2 = faces[0], faces[1]
imgnew = img.copy()
imgnew = swapper.get(imgnew, face1, face2, paste_back=True)
imgnew = swapper.get(imgnew, face2, face1, paste_back=True)
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
ax.imshow(imgnew[:,:,::-1])
ax.axis('off'); plt.show()
return imgnew
swap_faces('ТУТ ТВОЁ ИЗОБРАЖЕНИЕ')
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Dive into the world of tech with ⚔️🔍 TECH SOULS 👨💻🎯! We post about cool tech stuff like Y2038 bugs, clever pointers tricks, and sometimes, we post about AI. Join us for simple tutorials and explore the fun side of tech! 🚀
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