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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

Ko'proq ko'rsatish

📈 Telegram kanali Machine Learning analitikasi

Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 205 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 352-o'rinni va Suriya mintaqasida 228-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 40 205 obunachiga ega bo‘ldi.

02 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 343 ga, so‘nggi 24 soatda esa 10 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 1.99% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.28% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 800 marta ko‘riladi; birinchi sutkada odatda 915 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 03 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.

40 205
Obunachilar
+1024 soatlar
+837 kunlar
+34330 kunlar
Postlar arxiv
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I thought I’d read every secret manga out there… but last night I stumbled onto a title so wild it blew my mind. I can’t beli
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📌 Uncertainty in Markov Decisions Processes: a Robust Linear Programming approach 🗂 Category: MATH 🕒 Date: 2024-09-18 | ⏱️
📌 Uncertainty in Markov Decisions Processes: a Robust Linear Programming approach 🗂 Category: MATH 🕒 Date: 2024-09-18 | ⏱️ Read time: 8 min read Theoretical derivation of the Robust Counterpart of Markov Decision Processes (MDPs) as a Linear Program…

📌 Principal Component Analysis – Hands-On Tutorial 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-18 | ⏱️ Read time: 13 min read
📌 Principal Component Analysis – Hands-On Tutorial 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-18 | ⏱️ Read time: 13 min read Dimensionality reduction through Principal Component Analysis (PCA).

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📌 A Visual Exploration of Semantic Text Chunking 🗂 Category: NATURAL LANGUAGE PROCESSING 🕒 Date: 2024-09-19 | ⏱️ Read time
📌 A Visual Exploration of Semantic Text Chunking 🗂 Category: NATURAL LANGUAGE PROCESSING 🕒 Date: 2024-09-19 | ⏱️ Read time: 22 min read Use embeddings and visualization tools to split text into meaningful chunks

📌 Emerging Tech Is Nothing Without Methodology 🗂 Category: ANALYTICS 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Or: a H
📌 Emerging Tech Is Nothing Without Methodology 🗂 Category: ANALYTICS 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Or: a Hundred Ways to Solve a Complex Problem

📌 A Closer Look at Scipy’s Stats module – Part 1 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 7 min read Le
📌 A Closer Look at Scipy’s Stats module – Part 1 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 7 min read Let’s learn the main methods from scipy.stats module in Python.

📌 A Closer Look at Scipy’s Stats Module – Part 2 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Le
📌 A Closer Look at Scipy’s Stats Module – Part 2 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Let’s learn the main methods from scipy.stats module in Python.

📌 How to Build Your Own Roadmap for a Successful Data Science Career 🗂 Category: CAREER ADVICE 🕒 Date: 2024-09-19 | ⏱️ Rea
📌 How to Build Your Own Roadmap for a Successful Data Science Career 🗂 Category: CAREER ADVICE 🕒 Date: 2024-09-19 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

📌 The Evolution of Text to Video Models 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read Simplifyi
📌 The Evolution of Text to Video Models 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read Simplifying the neural nets behind Generative Video Diffusion

📌 AdEMAMix: A Deep Dive into a New Optimizer for Your Deep Neural Network 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-19
📌 AdEMAMix: A Deep Dive into a New Optimizer for Your Deep Neural Network 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-19 | ⏱️ Read time: 15 min read A better and faster option than the ADAM optimizer, from Apple Research

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📌 Shared Nearest Neighbors: A More Robust Distance Metric 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 36 min read A dis
📌 Shared Nearest Neighbors: A More Robust Distance Metric 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 36 min read A distance metric that can improve prediction, clustering, and outlier detection in datasets with many…

📌 Improving Code Quality with Array and DataFrame Type Hints 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 12 min read Ho
📌 Improving Code Quality with Array and DataFrame Type Hints 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 12 min read How generic specification permits powerful static and runtime validation

📌 Through the Uncanny Mirror: Do LLMs Remember Like the Human Mind? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-19
📌 Through the Uncanny Mirror: Do LLMs Remember Like the Human Mind? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read Exploring the Eerie Parallels and Profound Differences Between AI and Human Memory

📌 Mastering t-SNE: A Comprehensive Guide to Understanding and Implementation in Python 🗂 Category: DATA SCIENCE 🕒 Date: 20
📌 Mastering t-SNE: A Comprehensive Guide to Understanding and Implementation in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-20 | ⏱️ Read time: 26 min read Unlock the power of t-SNE for visualizing high-dimensional data, with a step-by-step Python implementation and…

📌 Choosing Between LLM Agent Frameworks 🗂 Category: 🕒 Date: 2024-09-20 | ⏱️ Read time: 15 min read Thanks to John Gilhuly
📌 Choosing Between LLM Agent Frameworks 🗂 Category: 🕒 Date: 2024-09-20 | ⏱️ Read time: 15 min read Thanks to John Gilhuly for his contributions to this piece. Agents are having a moment.…

📌 Paper Walkthrough: U-Net 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-20 | ⏱️ Read time: 16 min read A PyTorch implementati
📌 Paper Walkthrough: U-Net 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-20 | ⏱️ Read time: 16 min read A PyTorch implementation on one of the most popular semantic segmentation models.