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 68 566 obunachidan iborat bo'lib, Taʼlim toifasida 2 405-o'rinni va Hindiston mintaqasida 4 691-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 68 566 obunachiga ega bo‘ldi.
26 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 211 ga, so‘nggi 24 soatda esa -16 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 3.52% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.51% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 414 marta ko‘riladi; birinchi sutkada odatda 1 035 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 27 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.
68 566
Obunachilar
-1624 soatlar
-507 kun
+21130 kun
Postlar arxiv
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Repost from Machine Learning
I found a great resource for interactive learning about machine learning and AI – VizLearn.
You can experiment with gradient descent, SVM, PCA, the Bayesian method, BPE tokenization, Q/K/V, KV-cache, quantization, and much more. You can change the input data and see how the calculations themselves change.
It's free and doesn't require registration.
https://vizlearn.in
https://t.me/MachineLearning9
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
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@Omidyzd62
A collection of explanations for key concepts and scientific papers in machine learning:
https://github.com/dair-ai/ML-Papers-Explained
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Repost from Machine Learning
Pandas vs Polars — 14-section course cheatshee
https://t.me/MachineLearning9
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
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Repost from Machine Learning
Uniface
Automate face detection, recognition, and analysis of key facial landmarks with the Uniface Python library.
https://github.com/yakhyo/uniface
https://t.me/MachineLearning9
Repost from Machine Learning
OpenAI researcher Alice Liu went through 57 interviews before being hired, and then openly shared her entire preparation and job search journey.
If you're preparing for Research Scientist or MTS positions, this is one of the most comprehensive resources available.
You can use her notes directly, or simply use the list of topics to study them yourself. This kind of information is rarely published.
Notes on LLMs:
https://alisawuffles.notion.site/alisa-s-book-of-llms
Mathematics:
https://alisawuffles.notion.site/math-notes
Analysis of the job search and interview process:
https://alisawuffles.github.io/blog/job-search/
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#Programming #Coding #Development #Tech #Python #DataScienceRepost from Learn Python Coding
Here's a small fact about Python 🐍
The
:= operator is called the "walrus" because the symbols resemble the eyes and tusks of a walrus 🦭
It was introduced in Python 3.8 and allows you to assign a value to a variable and use it directly within the expression at the same time.
For example:
while (line := input("Say something: ")) != "quit":
print(f"You said: {line}")input(), and then check it.
Have you ever used the := operator in your code?
#Python #Programming #WalrusOperator #Coding #TechFacts #Python3
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