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
Tarmoq:📈 Telegram kanali Machine Learning with Python analitikasi
Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 68 521 obunachidan iborat bo'lib, Taʼlim toifasida 2 402-o'rinni va Hindiston mintaqasida 4 600-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 68 521 obunachiga ega bo‘ldi.
29 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 74 ga, so‘nggi 24 soatda esa -5 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 3.84% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.47% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 629 marta ko‘riladi; birinchi sutkada odatda 1 007 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 9 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 30 Oktabr, 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.
68 521
Obunachilar
-524 soatlar
-847 kun
+7430 kun
Postlar arxiv
+4
🚀 𝐄𝐩𝐨𝐜𝐡 𝐯𝐬 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 – 𝐓𝐡𝐞 𝐌𝐨𝐬𝐭 𝐂𝐨𝐦𝐦𝐨𝐧𝐥𝐲 𝐂𝐨𝐧𝐟𝐮𝐬𝐞𝐝 𝐓𝐞𝐫𝐦𝐬!
When training a neural network, two words confuse most beginners:
🔹 𝐄𝐩𝐨𝐜𝐡
𝘈𝘯 𝘦𝘱𝘰𝘤𝘩 𝘮𝘦𝘢𝘯𝘴 𝘵𝘩𝘦 𝘮𝘰𝘥𝘦𝘭 𝘩𝘢𝘴 𝘴𝘦𝘦𝘯 𝘵𝘩𝘦 𝘦𝘯𝘵𝘪𝘳𝘦 𝘥𝘢𝘵𝘢𝘴𝘦𝘵 𝘰𝘯𝘤𝘦.
𝘐𝘧 𝘺𝘰𝘶 𝘵𝘳𝘢𝘪𝘯 𝘧𝘰𝘳 10 𝘦𝘱𝘰𝘤𝘩𝘴, 𝘺𝘰𝘶𝘳 𝘮𝘰𝘥𝘦𝘭 𝘨𝘰𝘦𝘴 𝘵𝘩𝘳𝘰𝘶𝘨𝘩 𝘵𝘩𝘦 𝘸𝘩𝘰𝘭𝘦 𝘥𝘢𝘵𝘢 10 𝘵𝘪𝘮𝘦𝘴.
🔹 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧
𝘈𝘯 𝘪𝘵𝘦𝘳𝘢𝘵𝘪𝘰𝘯 𝘪𝘴 𝘰𝘯𝘦 𝘸𝘦𝘪𝘨𝘩𝘵 𝘶𝘱𝘥𝘢𝘵𝘦, 𝘣𝘢𝘴𝘦𝘥 𝘰𝘯 𝘢 𝘴𝘪𝘯𝘨𝘭𝘦 𝘣𝘢𝘵𝘤𝘩 𝘰𝘧 𝘥𝘢𝘵𝘢.
If you have:
10,000 𝘳𝘦𝘤𝘰𝘳𝘥𝘴
𝘉𝘢𝘵𝘤𝘩 𝘴𝘪𝘻𝘦 = 100
👉 𝘛𝘩𝘦𝘯 𝘺𝘰𝘶 𝘨𝘦𝘵 100 𝘪𝘵𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘴 𝘱𝘦𝘳 𝘦𝘱𝘰𝘤𝘩.
✔️ 𝐒𝐢𝐦𝐩𝐥𝐞 𝐀𝐧𝐚𝐥𝐨𝐠𝐲
𝐓𝐡𝐢𝐧𝐤 𝐨𝐟 𝐠𝐨𝐢𝐧𝐠 𝐭𝐨 𝐭𝐡𝐞 𝐠𝐲𝐦:
𝐄𝐩𝐨𝐜𝐡 = 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐞𝐧𝐭𝐢𝐫𝐞 𝐰𝐨𝐫𝐤𝐨𝐮𝐭 𝐩𝐥𝐚𝐧 𝐨𝐧𝐜𝐞
𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧 = 𝐝𝐨𝐢𝐧𝐠 𝐨𝐧𝐞 𝐬𝐞𝐭 𝐢𝐧𝐬𝐢𝐝𝐞 𝐭𝐡𝐚𝐭 𝐰𝐨𝐫𝐤𝐨𝐮𝐭
The model becomes stronger with every iteration, and improves overall with more epochs.
Read More: https://telegra.ph/Demystifying-Epochs--Iterations-in-Deep-Learning-11-24
👉 @codeprogrammer
Python For Data Science Cheat Sheet
#python #datascience #DataAnalysis
https://t.me/CodeProgrammer
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Amazing NumPy Cheat Sheet Snippet with 100 exercises for practicing the concept to get hands on to clear the coding round in the interviews
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Create a Wi-Fi QR code in Python in a couple of seconds
pip install wifi_qrcode_generatorimport 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")❔ 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().
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• 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
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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
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