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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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Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 191 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 381-o'rinni va Suriya mintaqasida 228-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 40 191 obunachiga ega bo‘ldi.

01 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 355 ga, so‘nggi 24 soatda esa 21 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 2.04% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.12% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 818 marta ko‘riladi; birinchi sutkada odatda 851 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 2 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 02 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.

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Postlar arxiv
📌 Optimizing Marketing Campaigns with Budgeted Multi-Armed Bandits 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-16 | ⏱️ Read t
📌 Optimizing Marketing Campaigns with Budgeted Multi-Armed Bandits 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-16 | ⏱️ Read time: 10 min read With demos, our new solution, and a video

📌 We Built an Open-Source Data Quality Testframework for PySpark 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-08-16 | ⏱️ Read
📌 We Built an Open-Source Data Quality Testframework for PySpark 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-08-16 | ⏱️ Read time: 6 min read Measure and report your data quality with ease

📌 Bad Assumptions – The Downfall of Even Experienced Data Scientists 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-16 | ⏱️ Read
📌 Bad Assumptions – The Downfall of Even Experienced Data Scientists 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-16 | ⏱️ Read time: 11 min read Data can be deceptive, so be on your toes!

📌 The Art of Chunking: Boosting AI Performance in RAG Architectures 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-18
📌 The Art of Chunking: Boosting AI Performance in RAG Architectures 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-18 | ⏱️ Read time: 1 min read The Key to Effective AI-Driven Retrieval

📌 The Art of Chunking: Boosting AI Performance in RAG Architectures 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-18
📌 The Art of Chunking: Boosting AI Performance in RAG Architectures 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-18 | ⏱️ Read time: 15 min read The Key to Effective AI-Driven Retrieval

📌 The Evolution of SQL 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-08-18 | ⏱️ Read time: 13 min read Unlocking the power of
📌 The Evolution of SQL 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-08-18 | ⏱️ Read time: 13 min read Unlocking the power of large language models

📌 The End of Required Work: Universal Basic Income and AI-Driven Prosperity 🗂 Category: 🕒 Date: 2024-08-19 | ⏱️ Read time:
📌 The End of Required Work: Universal Basic Income and AI-Driven Prosperity 🗂 Category: 🕒 Date: 2024-08-19 | ⏱️ Read time: 16 min read How a tax on AI work might let everyone share the imminent bounty from AI…

📌 Don’t Limit Your RAG Knowledgebase to Just Text 🗂 Category: BUSINESS 🕒 Date: 2024-08-19 | ⏱️ Read time: 8 min read Steal
📌 Don’t Limit Your RAG Knowledgebase to Just Text 🗂 Category: BUSINESS 🕒 Date: 2024-08-19 | ⏱️ Read time: 8 min read Steal this plug-n-play Python script to easily implement images into your chatbot’s Knowledgebase

📌 Unsupervised Learning Series: Exploring the Mean-Shift Algorithm 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-19
📌 Unsupervised Learning Series: Exploring the Mean-Shift Algorithm 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-19 | ⏱️ Read time: 11 min read Let’s learn one of the most famous density-based clustering algorithms, Mean-Shift.

📌 Speaker’s Privacy Protection in DNN-Based Speech Processing Tools 🗂 Category: 🕒 Date: 2024-08-20 | ⏱️ Read time: 11 min
📌 Speaker’s Privacy Protection in DNN-Based Speech Processing Tools 🗂 Category: 🕒 Date: 2024-08-20 | ⏱️ Read time: 11 min read A novel method in privacy-preserving speech processing which anonymizes the speaker attributes using space-filling vector…

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📌 K Nearest Neighbor Classifier, Explained: A Visual Guide with Code Examples for Beginners 🗂 Category: MACHINE LEARNING 🕒
📌 K Nearest Neighbor Classifier, Explained: A Visual Guide with Code Examples for Beginners 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-08-20 | ⏱️ Read time: 9 min read The friendly neighbor approach to machine learning

📌 Empowering Data-Driven Decisions: Embedding Trust in Text-to-SQL AI Agents 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2
📌 Empowering Data-Driven Decisions: Embedding Trust in Text-to-SQL AI Agents 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 19 min read Simplify complex data environments for users utilizing reliable AI Agent systems towards better data-driven decision-making

📌 Path Representation in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 5 min read Stop using strings
📌 Path Representation in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 5 min read Stop using strings to represent paths and use pathlib instead

📌 How to Effortlessly Extract Receipt Information with OCR and GPT-4o mini 🗂 Category: 🕒 Date: 2024-08-20 | ⏱️ Read time:
📌 How to Effortlessly Extract Receipt Information with OCR and GPT-4o mini 🗂 Category: 🕒 Date: 2024-08-20 | ⏱️ Read time: 16 min read Utilize OCR and the powerful GPT-4o mini model to perform information extraction on receipts

📌 Distance Metric Learning for Outlier Detection 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 23 min read A
📌 Distance Metric Learning for Outlier Detection 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 23 min read An outlier detection method that determines a relevant distance metric between records

📌 ChatGPT vs. Claude vs. Gemini for Data Analysis (Part 2): Who’s the Best at EDA? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 D
📌 ChatGPT vs. Claude vs. Gemini for Data Analysis (Part 2): Who’s the Best at EDA? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 14 min read Five criteria to compare ChatGPT, Claude, and Gemini in tackling Exploratory Data Analysis

📌 How to Forecast Hierarchical Time Series 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 13 min r
📌 How to Forecast Hierarchical Time Series 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 13 min read A beginner’s guide to forecast reconciliation

📌 Implementing Convolutional Neural Networks in TensorFlow 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-20 | ⏱️ Rea
📌 Implementing Convolutional Neural Networks in TensorFlow 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 6 min read Step-by-step code guide to building a Convolutional Neural Network

📌 Solving a Constrained Project Scheduling Problem with Quantum Annealing 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-20 | ⏱️
📌 Solving a Constrained Project Scheduling Problem with Quantum Annealing 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-20 | ⏱️ Read time: 29 min read Solving the resource constrained project scheduling problem (RCPSP) with D-Wave’s hybrid constrained quadratic model (CQM)