Endi mavjud! Telegram Tadqiqoti 2025 — yilning asosiy insaytlari 
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
Ko'proq ko'rsatish📈 Telegram kanali Machine Learning with Python analitikasi
Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 833 obunachidan iborat bo'lib, Taʼlim toifasida 2 428-o'rinni va Hindiston mintaqasida 5 035-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 67 833 obunachiga ega bo‘ldi.
15 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 82 ga, so‘nggi 24 soatda esa 13 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 4.40% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.74% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 983 marta ko‘riladi; birinchi sutkada odatda 1 177 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 5 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent insidead, learning, degree, evaluation, algorithm kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 16 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
67 833
Obunachilar
+1324 soatlar
+187 kunlar
+8230 kunlar
Postlar arxiv
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/DataScienceM
Django Roadmap
Link 1: https://github.com/HHHMHA/django-roadmap
Link 2:
https://github.com/faresemad/Django-Roadmap
قناة مهمة لكل مبرمج عم يبحث عن فرصة عمل او تدريب في مجال البرمجة او عندو رغبة بمتابعة tips او شروحات في مجال برمجة الويب او Problems solving
رابط القناة :
https://t.me/MGLNaJ
#MGLNaJ
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/DataScienceM
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A gentle introduction to K-Means Clustering in #R.
Featuring Tidyclust!
Enjoy.
https://www.business-science.io/code-tools/2023/07/06/kmeans-clustering.html?el=twitter
Important book
50 Algorithms Every Programmer Should Know (2023)
Read it
https://t.me/DataScienceM/286
Deep Learning
NLP
AI
Python
ML
Data Mining
Tensorflow
Keras
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@Machine_learn
Generative Adversarial Networks
https://realpython.com/generative-adversarial-networks
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
https://t.me/addlist/8_rRW2scgfRhOTc0
We launched a special bot some time ago to download all scientific, software and mathematics books The bot contains more than thirty million books, and new books are downloaded first, In addition to the possibility of downloading all articles and scientific papers for free
To request a subscription: talk to @Hussein_Sheikho
📩 Python Email Automation Script
import smtplib
from email.mime.text import MIMEText
sender_email = "your_email@example.com"
recipient_email = "recipient_email@example.com"
subject = "Automated Email"
message = "This is an automated email sent using Python."
# SMTP server configuration (example: Gmail)
smtp_server = "smtp.gmail.com"
smtp_port = 587
smtp_username = "your_username"
smtp_password = "your_password"
msg = MIMEText(message)
msg["Subject"] = subject
msg["From"] = sender_email
msg["To"] = recipient_email
try:
server = smtplib.SMTP(smtp_server, smtp_port)
server.starttls()
server.login(smtp_username, smtp_password)
server.sendmail(sender_email, recipient_email, msg.as_string())
print("Email sent successfully!")
except Exception as e:
print("Error sending email:", str(e))
finally:
server.quit()
https://t.me/DataScienceT