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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Tarmoq:📈 Telegram kanali Machine Learning analitikasi
Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 334 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 331-o'rinni va Suriya mintaqasida 225-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 40 334 obunachiga ega bo‘ldi.
10 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 383 ga, so‘nggi 24 soatda esa 25 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
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- Jalb etish (ER): Auditoriya o‘rtacha 2.35% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.95% ini tashkil etuvchi reaksiyalarni to‘playdi.
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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 11 Iyul, 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.
40 334
Obunachilar
+2524 soatlar
+1227 kunlar
+38330 kunlar
Postlar arxiv
40 334
📌 Step-by-Step Guide to Build and Deploy an LLM-Powered Chat with Memory in Streamlit
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-05-01 | ⏱️ Read time: 17 min read
And monitor your API usage on Google Cloud Console
40 334
📌 A Farewell to APMs — The Future of Observability is MCP tools
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-01 | ⏱️ Read time: 10 min read
Like many other fields, the world of observability is about to be turned upside down
40 334
📌 Rust for Python Developers: Why You Should Take a Look at the Rust Programming Language
🗂 Category: PROGRAMMING
🕒 Date: 2025-05-02 | ⏱️ Read time: 13 min read
Discover how Rust complements Python with speed, safety, and control — and why it’s worth…
40 334
📌 Agentic AI 101: Starting Your Journey Building AI Agents
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-02 | ⏱️ Read time: 12 min read
Learn the fundamentals of how to create AI Agents.
40 334
📌 Talking to Kids About AI
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-02 | ⏱️ Read time: 16 min read
“This is your brain on an LLM”, and other things you shouldn’t say
40 334
📌 Want Better Clusters? Try DeepType
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-02 | ⏱️ Read time: 9 min read
A smarter way to cluster data using deep learning
40 334
📌 The Difference between Duplicate and Reference in Power Query
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-05-02 | ⏱️ Read time: 9 min read
In Power Query, we can duplicate or reference existing tables. But what are the differences…
40 334
📌 Why I stopped Using Cursor and Reverted to VSCode
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-02 | ⏱️ Read time: 6 min read
Is GitHub Copilot the best AI-assistant for Data Scientists?
40 334
📌 The Shape‑First Tune‑Up Provides Organizations with a Means to Reduce MongoDB Expenses by 79%
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-05-02 | ⏱️ Read time: 9 min read
A real-world engineering fix that saved over $12K/month on MongoDB without upgrading infrastructure.
40 334
📌 Attaining LLM Certainty with AI Decision Circuits
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-05-02 | ⏱️ Read time: 15 min read
Uncertainty is nothing new in technology — all modern systems overcome uncertain inputs and outputs…
40 334
📌 Build and Query Knowledge Graphs with LLMs
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-05-02 | ⏱️ Read time: 28 min read
Going from document ingestion to smart queries — all with open tools and guided setup
40 334
📌 From a Point to L∞
🗂 Category: MATH
🕒 Date: 2025-05-02 | ⏱️ Read time: 9 min read
How AI uses distance
40 334
📌 Website Feature Engineering at Scale: PySpark, Python & Snowflake
🗂 Category: DATA SCIENCE
🕒 Date: 2025-05-05 | ⏱️ Read time: 9 min read
Introduction and Problem Imagine you’re staring at a database containing thousands of merchants across multiple…
40 334
📌 Fine-Tuning vLLMs for Document Understanding
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-05-05 | ⏱️ Read time: 25 min read
Learn how you can fine-tune visual language models for specific tasks
40 334
📌 Making Sense of KPI Changes
🗂 Category: DATA SCIENCE
🕒 Date: 2025-05-05 | ⏱️ Read time: 15 min read
A practical guide to understanding what’s really going on
40 334
📌 Diffusion Models, Explained Simply
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-05 | ⏱️ Read time: 7 min read
From noise to art: how to generate high-quality images using diffusion models
40 334
📌 The CNN That Challenges ViT | ConvNeXt
🗂 Category: DEEP LEARNING
🕒 Date: 2025-05-05 | ⏱️ Read time: 24 min read
A PyTorch implementation on the ConvNeXt architecture
40 334
📌 Think. Know. Act. How AI’s Core Capabilities Will Shape the Future of Work
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-05-06 | ⏱️ Read time: 13 min read
It’s not just about technical depth, it’s about strategic clarity
40 334
📌 Benchmarking Tabular Reinforcement Learning Algorithms
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-05-06 | ⏱️ Read time: 27 min read
Comparing all methods from Part I of Sutton’s book on gridworld environments
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📌 Make Your Data Move: Creating Animations in Python for Science and Machine Learning
🗂 Category: DATA VISUALIZATION
🕒 Date: 2025-05-06 | ⏱️ Read time: 6 min read
Go beyond static plots with matplotlib.
