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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Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 819 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, 67 819 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 06 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.

67 819

Obunachilar

+924 soatlar

+587 kunlar

+7730 kunlar

1 767

Post ko'rishlar

~ 1 69524 soatlar

~ 2 25748 soatlar

2.60%

Muloqot nisbati

~ 3

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Repost from Python Courses & Resources

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🔖 An excellent resource for learning about neural networks We're sharing a cool resource for learning about neural networks, offering clear, step-by-step instruction with dynamic visualizations and easy-to-understand explanations. In addition, you'll find many other useful materials on machine learning on the site. Find and use it — https://mlu-explain.github.io/neural-networks/ tags: #AI #ML #PYTHON ➡ @CODEPROGRAMMER

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Repost from Machine Learning

📌 Your First 90 Days as a Data Scientist 🗂 Category: DATA SCIENCE 🕒 Date: 2026-02-14 | ⏱️ Read time: 8 min read A practical onboarding checklist for building trust, business fluency, and data intuition #DataScience #AI #Python

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Design patterns are proven solutions to common problems in development. If you've ever found yourself constantly writing the same thing when creating objects or struggling with managing different types of objects, then the factory pattern might be exactly what you need. In this tutorial: https://www.freecodecamp.org/news/how-to-use-the-factory-pattern-in-python-a-practical-guide/ you'll learn what a factory is, why it's useful, and how to implement it in #Python. We'll gather practical examples that will show when and how to apply this pattern in real tasks. The code can be found on #GitHub https://github.com/balapriyac/python-basics/tree/main/design-patterns/factory https://t.me/CodeProgrammer

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Repost from Data Analytics

These 9 lectures from Stanford are a pure goldmine for anyone wanting to learn and understand LLMs in depth Lecture 1 - Transformer: https://lnkd.in/dGnQW39t Lecture 2 - Transformer-Based Models & Tricks: https://lnkd.in/dT_VEpVH Lecture 3 - Tranformers & Large Language Models: https://lnkd.in/dwjjpjaP Lecture 4 - LLM Training: https://lnkd.in/dSi_xCEN Lecture 5 - LLM tuning: https://lnkd.in/dUK5djpB Lecture 6 - LLM Reasoning: https://lnkd.in/dAGQTNAM Lecture 7 - Agentic LLMs: https://lnkd.in/dWD4j7vm Lecture 8 - LLM Evaluation: https://lnkd.in/ddxE5zvb Lecture 9 - Recap & Current Trends: https://lnkd.in/dGsTd8jN Start understanding #LLMs in depth from the experts. Go through each step-by-step video. https://t.me/DataAnalyticsX 🔗

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