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:Machine Learning with Python Suriya225 Texnologiyalar & Aralashmalar3 332...

📈 Telegram kanali Machine Learning analitikasi

Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 310 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 332-o'rinni va Suriya mintaqasida 225-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 40 310 obunachiga ega bo‘ldi.

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

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 2.23% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.95% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 897 marta ko‘riladi; birinchi sutkada odatda 788 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 10 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.

40 310

Obunachilar

+3024 soatlar

+1067 kunlar

+37830 kunlar

897

Post ko'rishlar

~ 78824 soatlar

~ 1 02448 soatlar

2.23%

Muloqot nisbati

~ 2

Kuniga postlar

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Postlar arxiv

40 310

📌 No Peeking Ahead: Time-Aware Graph Fraud Detection 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-14 | ⏱️ Read time: 15 min read How to implement leak-free graph fraud detection

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What if you could unlock the secrets behind every glass of wine you sip? Discover rare finds, honest reviews, and the fascinating stories of wine regions — without the snobbery. Whether you’re a connoisseur or simply love exploring new tastes, join Simply Wine | Great Wine Lover for insights you won’t find anywhere else. Ready to swirl, sniff, and savor? Dive in now! #ad InsideAds

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📌 Using Optimization to Solve Adversarial Problems 🗂 Category: 🕒 Date: 2025-01-14 | ⏱️ Read time: 41 min read An example of simultaneously optimizing two policies for two adversarial agents, looking specifically at the…

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📌 You Think 80% Means 80%? Why Prediction Probabilities Need a Second Look 🗂 Category: 🕒 Date: 2025-01-14 | ⏱️ Read time: 9 min read Understand the gap between predicted probabilities and real-world outcomes

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📌 From Darwin to Deep Work 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 7 min read Focus Strategies for Machine Learning Practitioners

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📌 Why Normalization Is Crucial for Policy Evaluation in Reinforcement Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-01-14 | ⏱️ Read time: 6 min read Enhancing Accuracy in Reinforcement Learning Policy Evaluation through Normalization

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📌 Scale Experiment Decision-Making with Programmatic Decision Rules 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 6 min read Decide what to do with experiment results in code

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📌 How To: Forecast Time Series Using Lags 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 8 min read Lag columns can significantly boost your model’s performance

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📌 Hands-On Delivery Routes Optimization (TSP) with AI, Using LKH and Python 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 12 min read Here’s how to optimize the delivery routes, from theory to code.

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📌 Basics of GANs & SMOTE for Data Augmentation 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-15 | ⏱️ Read time: 14 min read GANs and SMOTE Explained with Bartending: Data Science for Machine Learning Series (1)

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📌 Scaling Segmentation with Blender: How to Automate Dataset Creation 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-15 | ⏱️ Read time: 10 min read A Step-by-Step Guide to Generating Synthetic Data for Training AI Models

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📌 LossVal Explained: Efficiently Estimate the Importance of Your Training Data 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-15 | ⏱️ Read time: 7 min read How to Exploit the Loss Function for Efficient Data Valuation

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📌 Recursive Walks down User Referral Trees 🗂 Category: MARKETING 🕒 Date: 2025-01-15 | ⏱️ Read time: 6 min read Measuring the total influence of users in a user referral program by traversing indirect referrals

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📌 Unlocking the Power of Machine Learning in Analytics: Practical Use Cases and Skills 🗂 Category: ANALYTICS 🕒 Date: 2025-01-15 | ⏱️ Read time: 9 min read Your essential machine learning checklist to excel as a data scientist in analytics

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📌 Understanding Flash Attention: Writing the Algorithm from Scratch in Triton 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-01-15 | ⏱️ Read time: 7 min read Find out how Flash Attention works. Afterward, we’ll refine our understanding by writing a GPU…

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📌 What Did I Learn from Building LLM Applications in 2024? – Part 2 🗂 Category: 🕒 Date: 2025-01-17 | ⏱️ Read time: 13 min read An engineer’s journey to building LLM-powered applications

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📌 Influential Time-Series Forecasting Papers of 2023-2024: Part 1 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-01-17 | ⏱️ Read time: 16 min read Exploring the latest advancements in time series