پایتون | Data Science | Machine Learning
◀️اینجا با تمرین و چالش با هم پایتون رو یاد می گیریم ⏮بانک اطلاعاتی پایتون پروژه / code/ cheat sheet +ویدیوهای آموزشی +کتابهای پایتون تبلیغات: @alloadv 🔁ادمین : @maryam3771
Show more📈 Analytical overview of Telegram channel پایتون | Data Science | Machine Learning
Channel پایتون | Data Science | Machine Learning (@python4all_pro) in the Farsi language segment is an active participant. Currently, the community unites 24 006 subscribers, ranking 5 487 in the Technologies & Applications category and 14 629 in the Iran region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 24 006 subscribers.
According to the latest data from 24 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -312 over the last 30 days and by -15 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.22%. Within the first 24 hours after publication, content typically collects 1.39% reactions from the total number of subscribers.
- Post reach: On average, each post receives 532 views. Within the first day, a publication typically gains 335 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
- Thematic interests: Content is focused on key topics such as مصنوعی, دنیا, آموزش, پایتون, وبینار.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“◀️اینجا با تمرین و چالش با هم پایتون رو یاد می گیریم
⏮بانک اطلاعاتی پایتون
پروژه / code/ cheat sheet
+ویدیوهای آموزشی
+کتابهای پایتون
تبلیغات:
@alloadv
🔁ادمین :
@maryam3771”
Thanks to the high frequency of updates (latest data received on 25 October, 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 Technologies & Applications category.
pip install pillow
Then, use this script:
from PIL import Image
in_img = 'input.jpg'
out_img = 'grayscale.jpg'
# Open the image
with Image.open(in_img) as img:
# Convert the image to grayscale
grayscale_img = img.convert('L')
# Save the grayscale image
grayscale_img.save(out_img)import ChatTTS
from IPython.display import Audio
chat = ChatTTS.Chat()
chat.load_models()
texts = ["<PUT YOUR TEXT HERE>",]
wavs = chat.infer(texts, use_decoder=True)
Audio(wavs[0], rate=24_000, autoplay=True)
ChatTTS is a text-to-speech model designed specifically for conversational scenarios such as LLM assistant.
ChatTTS supports both English and Chinese (if relevant).
🖥 GitHub
👉 Hugging Face
👉 ChatTTS page
🆔 @Python4all_pro# pip install rembg pillow
from rembg import remove
from PIL import Image
input_path = "in.png"
output_path = "out.png"
input = Image.open(input_path)
output = remove(input)
output.save(output_path)
https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx
🆔 @Python4all_pro