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 Suriya227 Texnologiyalar & Aralashmalar3 343...

📈 Telegram kanali Machine Learning analitikasi

Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 244 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 343-o'rinni va Suriya mintaqasida 227-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 40 244 obunachiga ega bo‘ldi.

05 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 346 ga, so‘nggi 24 soatda esa 22 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 1.97% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.86% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 794 marta ko‘riladi; birinchi sutkada odatda 749 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 06 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.

40 244

Obunachilar

+2224 soatlar

+987 kunlar

+34630 kunlar

794

Post ko'rishlar

~ 74924 soatlar

~ 98448 soatlar

1.97%

Muloqot nisbati

~ 3

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📌 A Story of Long Tails: Why Uncertainty in Marketing Mix Modelling is Important 🗂 Category: MARKETING 🕒 Date: 2024-11-27 | ⏱️ Read time: 30 min read "Details matter. It’s worth waiting to get it right." — Steve Jobs What if the…

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📌 Saving Pandas DataFrames Efficiently and Quickly – Parquet vs Feather vs ORC vs CSV 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 15 min read Speed, RAM, size and convenience. Which storage method is best?

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📌 Use Tablib to Handle Simple Tabular Data in Python 🗂 Category: 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Sometimes a Shallow Abstraction is more Valuable than Performance

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📌 Introducing the New Anthropic PDF Processing API 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read Anthropic Claude 3.5 now understands PDF input

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📌 Roadmap to Becoming a Data Scientist, Part 1: Maths 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Identifying fundamental math skills to master for aspiring Data Scientists

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📌 How to Develop an Effective AI-Powered Legal Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-11-27 | ⏱️ Read time: 13 min read Create a machine-learning-based search into legal decisions

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📌 Level Up Your Coding Skills with Python Threading 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read Learn how to use queues, daemon threads, and events in a Machine Learning project

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📌 Effortless Data Handling: Find Variables Across Multiple Data Files with R 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 8 min read A practical solution with code and workflow

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📌 AI Agents in Networking Industry 🗂 Category: 🕒 Date: 2024-11-27 | ⏱️ Read time: 11 min read AI Agents for deploying, configuring and monitoring Networks

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📌 How to Prune LLaMA 3.2 and Similar Large Language Models 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-11-27 | ⏱️ Read time: 17 min read This article presents a structured pruning technique for state-of-the-art models, that uses a GLU architecture,…

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📌 How to Transition from Engineering to Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-27 | ⏱️ Read time: 7 min read AI for engineers: experience of an engineering graduate

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📌 How Can Self-Driving Cars Work Better? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-28 | ⏱️ Read time: 8 min read The far-reaching implications of Waymo’s EMMA and other end-to-end driving systems

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📌 How to Select the 5 Most Relevant Documents for AI Search 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-19 | ⏱️ Read time: 10 min read Improve the document retrieval step of your RAG pipeline

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📌 An Interactive Guide to 4 Fundamental Computer Vision Tasks Using Transformers 🗂 Category: COMPUTER VISION 🕒 Date: 2025-09-19 | ⏱️ Read time: 14 min read An overview of 4 fundamental computer vision tasks – image classification, image segmentation, image captioning…

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📌 LLMs.txt Explained 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-28 | ⏱️ Read time: 6 min read Your guide to the web’s new LLM-ready content standard

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Я получил свои первые TON за 5 минут — и ничем не рисковал! «Думал, что это очередной фейк… но TON реально пришли на счет» Хочешь также? Узнай, как получить до 10 TON без вложений — уже сегодня. #ad InsideAds .

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📌 The Economics of Artificial Intelligence – what does automation mean for workers? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-25 | ⏱️ Read time: 40 min read Despite tremendous progress in AI, the economic implications of AI remain inadequately understood, with unsatisfactory…

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📌 RAGOps Guide: Building and Scaling Retrieval Augmented Generation Systems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-11-26 | ⏱️ Read time: 28 min read The Architecture, Operational Layers, and Best Practices for Effective RAG Implementation

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📌 Every Step of the Machine Learning Life Cycle Simply Explained 🗂 Category: DATA SCIENCE 🕒 Date: 2024-11-26 | ⏱️ Read time: 18 min read A comprehensive guide to the ML life cycle with examples in Python

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“Sadece 8 PUMP ile işlem başlatabileceğini kimse bana inanmamıştı!” Her referans 2 PUMP veriyor, görevleri tamamla ve sırrı burada keşfet — kimse fark etmeden airdropları topla! #ad InsideAds