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 24 706 subscribers, ranking 5 515 in the Technologies & Applications category and 13 715 in the Iran region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 24 706 subscribers.
According to the latest data from 18 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 1 596 over the last 30 days and by -10 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.81%. Within the first 24 hours after publication, content typically collects 2.09% reactions from the total number of subscribers.
- Post reach: On average, each post receives 941 views. Within the first day, a publication typically gains 515 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
- 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 19 June, 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.
%load_ext cudf.pandas
import pandas as pd
GitHub : https://github.com/rapidsai/cudf
#library
#Python_tricks
🆔 @Python4all_proimport os
directory = 'path/to/your/folder'
prefix = 'image_'
# Iterate over files in the directory
for count, filename in enumerate(os.listdir(directory)):
new_name = f"{prefix}{count}.png"
src = f"{directory}/{filename}"
dst = f"{directory}/{new_name}"
# Rename the file
os.rename(src, dst)pip install deepchem
؛DeepChem مجموعه ای عالی از ابزارهای منبع باز را ارائه می دهد که با استفاده از یادگیری عمیق برای کشف دارو، علم مواد، شیمی کوانتومی و زیست شناسی ساخته دیده است
🖥 GitHub
👉Tutorials
👉 Deep Learning Models from DeepChem
🆔 @Python4all_pro# Importing necessary libraries
import PyPDF2
import pyttsx3
# Prompt user for the PDF file name
pdf_filename = input("Enter the PDF file name (including extension): ").strip()
# Open the PDF file
try:
with open(pdf_filename, 'rb') as pdf_file:
# Create a PdfFileReader object
pdf_reader = PyPDF2.PdfReader(pdf_file)
# Get an engine instance for the speech synthesis
speak = pyttsx3.init()
# Iterate through each page and read the text
for page_num in range(len(pdf_reader.pages)):
page = pdf_reader.pages[page_num]
text = page.extract_text()
if text:
speak.say(text)
speak.runAndWait()
# Stop the speech engine
speak.stop()
print("Audiobook creation completed.")
except FileNotFoundError:
print("The specified file was not found.")
except Exception as e:
print(f"An error occurred: {e}")
🆔 @Python4all_propip 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
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