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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Tarmoq:Machine Learning with Python Hindiston5 049 Taʼlim2 404...

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Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 821 obunachidan iborat bo'lib, Taʼlim toifasida 2 404-o'rinni va Hindiston mintaqasida 5 049-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 67 821 obunachiga ega bo‘ldi.

05 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 77 ga, so‘nggi 24 soatda esa 9 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 2.60% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.50% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 1 767 marta ko‘riladi; birinchi sutkada odatda 1 695 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 6 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 07 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.

67 821

Obunachilar

+924 soatlar

+587 kunlar

+7730 kunlar

1 767

Post ko'rishlar

~ 1 69524 soatlar

~ 2 25748 soatlar

2.60%

Muloqot nisbati

~ 3

Kuniga postlar

Ads index

beta

Postlar arxiv

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Have you tried running the code? yes 👍 | No 👎

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Create a Wi-Fi QR code in Python in a couple of seconds

pip install wifi_qrcode_generator

import wifi_qrcode_generator.generator
from PIL import Image

ssid = "CLCoding_WIFI"
password = "supersecret123"
security = "WPA"

from wifi_qrcode_generator.generator import wifi_qrcode
qr = wifi_qrcode(ssid, False, security, password)

qr.make_image().save("wifi_qr.png")
Image.open("wifi_qr.png")

👉 @codeprogrammer

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❔ Interview question What do globals() and locals() do? Answer: Functions globals() and locals() return a dictionary with variables of the current scope. ▶️ globals() — provides access to all global names in the current module (i.e., variables, functions, and classes defined at the top level) ▶️ locals() — returns local variables in the current context: inside a function, class, or block They are useful for dynamic analysis, debugging, metaprogramming, and when working with eval() / exec(). tags: #interview ➡ @codeprogrammer

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Your interaction with us drives us more free information and knowledge

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This GitHub repo is a gold mine for EVERY data scientist! (full of hands-on and interactive tutorials) DS Interactive Python provides several dashboards to interactively learn about statistics, ML models, and other related theoretical concepts! Some key topics you can understand interactively: • PCA • Bagging and boosting • Linear regression and OLS • Bayesian and frequentist statistics • confidence intervals • clustering (kmeans, spectral clustering, etc.) • central limit theorem • neural networks (the backpropagation animation is really good) • and many more. Link: https://github.com/GeostatsGuy/DataScienceInteractivePython https://t.me/CodeProgrammer

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Repost from Python Courses & Resources

Create artificial intelligence using Python In the video the author explains the basics of neural networks and shows how to implement your own simple #AI from scratch in #Python

https://t.me/Python53

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Repost from Machine Learning with Python

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Data Science Formulas Cheat Sheet.pdf1.75 KB

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https://t.me/DataScienceY

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Comprehensive Python Cheatsheet This Comprehensive #Python Cheatsheet brings together core syntax, data structures, functions, #OOP, decorators, regular expressions, libraries, and more — neatly organized for quick reference and deep understanding.

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