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Machine Learning

Machine Learning

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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Telegram kanali Machine Learning analitikasi

Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 145 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 375-o'rinni va Suriya mintaqasida 227-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 40 145 obunachiga ega bo‘ldi.

28 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 378 ga, so‘nggi 24 soatda esa 7 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 2.09% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.91% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 841 marta ko‘riladi; birinchi sutkada odatda 766 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 3 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent distance, insidead, gpu, learning, degree kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Yuqori yangilanish chastotasi (oxirgi ma’lumot 29 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

40 145
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Postlar arxiv
📚 Readers Unity – Ek jagah, 13,000+ books ek sath! 🔹 Free PDF & e-Books 🔹 Hindi aur English dono language 🔹 Novels, motiv
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📌 Benchmarking LLM Inference Backends 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-17 | ⏱️ Read time: 12 min read Comparin
📌 Benchmarking LLM Inference Backends 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-17 | ⏱️ Read time: 12 min read Comparing Llama 3 serving performance on vLLM, LMDeploy, MLC-LLM, TensorRT-LLM, and TGI

📌 Data Privacy in AI Development: Data Localization 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-06-18 | ⏱️ Read time: 14 min
📌 Data Privacy in AI Development: Data Localization 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-06-18 | ⏱️ Read time: 14 min read Why should you care where your data lives?

📌 The Important Role of Memory in Agentic AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-18 | ⏱️ Read time: 6 min
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📌 Statistically Confirm Your -Comparing Pandas and Polars with 1 Million Rows of Data 🗂 Category: DATA SCIENCE 🕒 Date: 202
📌 Statistically Confirm Your -Comparing Pandas and Polars with 1 Million Rows of Data 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-18 | ⏱️ Read time: 15 min read Using the Independent samples t-test and Welch’s t-test to compare scores in benchmarking.

📌 Chart Wars – Stacked Bar Chart vs. Heatmap 🗂 Category: DATA VISUALIZATION 🕒 Date: 2024-06-18 | ⏱️ Read time: 6 min read
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📌 Get started with SQLite3 in Python Creating Tables & Fetching Rows 🗂 Category: SQL 🕒 Date: 2024-06-18 | ⏱️ Read time: 12
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📌 8 Years in Data: What I Wish I’d Known from the Start 🗂 Category: CAREER ADVICE 🕒 Date: 2024-06-18 | ⏱️ Read time: 5 min
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📌 A Proposed Perfect Package Prototype for Python Projects 🗂 Category: PROGRAMMING 🕒 Date: 2024-06-18 | ⏱️ Read time: 17 m
📌 A Proposed Perfect Package Prototype for Python Projects 🗂 Category: PROGRAMMING 🕒 Date: 2024-06-18 | ⏱️ Read time: 17 min read How to structure your Python package projects to ensure efficiency, effectiveness and future-proofing

📌 PySpark Explained: The explode and collect_list Functions 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-06-18 | ⏱️ Read time
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📌 How to Find and Solve Valuable Generative AI Use Cases 🗂 Category: PRODUCT MANAGEMENT 🕒 Date: 2024-06-18 | ⏱️ Read time:
📌 How to Find and Solve Valuable Generative AI Use Cases 🗂 Category: PRODUCT MANAGEMENT 🕒 Date: 2024-06-18 | ⏱️ Read time: 7 min read 80% of AI projects fail due to poor use cases or technical knowledge. Gen AI…

📌 Nailing the Machine Learning Design Interview 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-18 | ⏱️ Read time: 9 min read
📌 Nailing the Machine Learning Design Interview 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-18 | ⏱️ Read time: 9 min read Tips and tricks for FAANG design interviews

📌 Incorporate an LLM Chatbot into Your Web Application with OpenAI, Python, and Shiny 🗂 Category: 🕒 Date: 2024-06-18 | ⏱️
📌 Incorporate an LLM Chatbot into Your Web Application with OpenAI, Python, and Shiny 🗂 Category: 🕒 Date: 2024-06-18 | ⏱️ Read time: 8 min read Step-by-Step Integration of AI Chatbots into Shiny for Python Applications: From API Setup to User…

📌 Human Won’t Replace Python 🗂 Category: PROGRAMMING 🕒 Date: 2025-10-14 | ⏱️ Read time: 23 min read Why vibe-coding is not
📌 Human Won’t Replace Python 🗂 Category: PROGRAMMING 🕒 Date: 2025-10-14 | ⏱️ Read time: 23 min read Why vibe-coding is not a step up from “classic” coding — and why it matters

📌 Why AI Still Can’t Replace Analysts: A Predictive Maintenance Example 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-1
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📌 Building A Successful Relationship With Stakeholders 🗂 Category: DATA SCIENCE 🕒 Date: 2025-10-14 | ⏱️ Read time: 12 min
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📌 Learning Triton One Kernel at a Time: Matrix Multiplication 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-10-14 | ⏱️ Read ti
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📌 Foundation Models in Graph & Geometric Deep Learning 🗂 Category: 🕒 Date: 2024-06-18 | ⏱️ Read time: 28 min read In this
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📌 Managing Pivot Table and Excel Charts with VBA 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-18 | ⏱️ Read time: 10 min read S
📌 Managing Pivot Table and Excel Charts with VBA 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-18 | ⏱️ Read time: 10 min read Save precious hours by automating working with pivot tables and charts using VBA

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