uz
Feedback
Machine Learning

Machine Learning

Kanalga Telegram’da o‘tish

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 40 100 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 398-o'rinni va Suriya mintaqasida 232-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 40 100 obunachiga ega bo‘ldi.

23 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 379 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 1.92% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.16% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 770 marta ko‘riladi; birinchi sutkada odatda 466 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 24 Iyun, 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.

40 100
Obunachilar
+3024 soatlar
+337 kunlar
+37930 kunlar
Postlar arxiv
💛 Top 10 Best Websites to Learn Machine Learning ⭐️ by [@codeprogrammer] --- 🧠 Google’s ML Course 🔗 https://developers.google.com/machine-learning/crash-course 📈 Kaggle Courses 🔗 https://kaggle.com/learn 🧑‍🎓 Coursera – Andrew Ng’s ML Course 🔗 https://coursera.org/learn/machine-learning ⚡️ Fast.ai 🔗 https://fast.ai 🔧 Scikit-Learn Documentation 🔗 https://scikit-learn.org 📹 TensorFlow Tutorials 🔗 https://tensorflow.org/tutorials 🔥 PyTorch Tutorials 🔗 https://docs.pytorch.org/tutorials/ 🏛️ MIT OpenCourseWare – Machine Learning 🔗 https://ocw.mit.edu/courses/6-867-machine-learning-fall-2006/ ✍️ Towards Data Science (Blog) 🔗 https://towardsdatascience.com --- 💡 Which one are you starting with? Drop a comment below! 👇 #MachineLearning #LearnML #DataScience #AI https://t.me/CodeProgrammer 🌟

📌 Layered Architecture for Building Readable, Robust, and Extensible Apps 🗂 Category: SOFTWARE ENGINEERING 🕒 Date: 2026-01
📌 Layered Architecture for Building Readable, Robust, and Extensible Apps 🗂 Category: SOFTWARE ENGINEERING 🕒 Date: 2026-01-27 | ⏱️ Read time: 11 min read If adding a feature feels like open-heart surgery on your codebase, the problem isn’t bugs,… #DataScience #AI #Python

📌 From Connections to Meaning: Why Heterogeneous Graph Transformers (HGT) Change Demand Forecasting 🗂 Category: DATA SCIENC
📌 From Connections to Meaning: Why Heterogeneous Graph Transformers (HGT) Change Demand Forecasting 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-27 | ⏱️ Read time: 12 min read How relationship-aware graphs turn connected forecasts into operational insight #DataScience #AI #Python

📌 Data Science as Engineering: Foundations, Education, and Professional Identity 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-
📌 Data Science as Engineering: Foundations, Education, and Professional Identity 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-27 | ⏱️ Read time: 15 min read Recognize data science as an engineering practice and structure education accordingly. #DataScience #AI #Python

📌 Going Beyond the Context Window: Recursive Language Models in Action 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-2
📌 Going Beyond the Context Window: Recursive Language Models in Action 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-27 | ⏱️ Read time: 24 min read Explore a practical approach to analysing massive datasets with LLMs #DataScience #AI #Python

📌 How Convolutional Neural Networks Learn Musical Similarity 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-26 | ⏱️ Read tim
📌 How Convolutional Neural Networks Learn Musical Similarity 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-26 | ⏱️ Read time: 13 min read Learning audio embeddings with contrastive learning and deploying them in a real music recommendation app #DataScience #AI #Python

📌 Ray: Distributed Computing For All, Part 2 🗂 Category: PROGRAMMING 🕒 Date: 2026-01-26 | ⏱️ Read time: 11 min read Deploy
📌 Ray: Distributed Computing For All, Part 2 🗂 Category: PROGRAMMING 🕒 Date: 2026-01-26 | ⏱️ Read time: 11 min read Deploying and running Python code on cloud-based clusters #DataScience #AI #Python

📌 How Cursor Actually Indexes Your Codebase 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-26 | ⏱️ Read time: 10 min re
📌 How Cursor Actually Indexes Your Codebase 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-26 | ⏱️ Read time: 10 min read Exploring the RAG pipeline in Cursor that powers code indexing and retrieval for coding agents #DataScience #AI #Python

📌 Causal ML for the Aspiring Data Scientist 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-26 | ⏱️ Read time: 18 min read An
📌 Causal ML for the Aspiring Data Scientist 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-26 | ⏱️ Read time: 18 min read An accessible introduction to causal inference and ML #DataScience #AI #Python

Data Science Interview questions #DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience #DataAnalysis #LLM #InterviewQuestions https://t.me/CodeProgrammer

📌 SAM 3 vs. Specialist Models — A Performance Benchmark 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-25 | ⏱️ Read time: 19
📌 SAM 3 vs. Specialist Models — A Performance Benchmark 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-25 | ⏱️ Read time: 19 min read Why specialized models still hold the 30x speed advantage in production environments #DataScience #AI #Python

📌 Azure ML vs. AWS SageMaker: A Deep Dive into Model Training — Part 1 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-25 | ⏱
📌 Azure ML vs. AWS SageMaker: A Deep Dive into Model Training — Part 1 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-25 | ⏱️ Read time: 11 min read Compare Azure ML and AWS SageMaker for scalable model training, focusing on project setup, permission… #DataScience #AI #Python

📌 Air for Tomorrow: Mapping the Digital Air-Quality Landscape, from Repositories and Data Types to Starter Code 🗂 Category:
📌 Air for Tomorrow: Mapping the Digital Air-Quality Landscape, from Repositories and Data Types to Starter Code 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-24 | ⏱️ Read time: 25 min read Understand air quality: access the available data, interpret data types, and execute starter codes #DataScience #AI #Python

Listen, if you’re tired of those sketchy Forex signals that drain your account faster than your morning coffee, check this ou
Listen, if you’re tired of those sketchy Forex signals that drain your account faster than your morning coffee, check this out. At FREE | Forex Hollywood, we keep it simple: just 1TP and 1SL, no mess, all profit. This week? We nailed +500 PIPS, five days straight. Yep, others lose, we win. Wanna trade smarter, not harder? Join us and see why our analysis and strategy crush the rest. No fluff, just legit gains. Slide into @Forex_Hollywood and start winning today. 🎯 Join FREE | Forex Hollywood #ad InsideAds

Ant AI Automated Sales Robot is an intelligent robot focused on automating lead generation and sales conversion. Its core function simulates human conversation, achieving end-to-end business conversion and easily generating revenue without requiring significant time investment. I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion" Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention. High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments. 24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time. II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open. Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits. If you are interested, please join my Telegram group for more information and leave a message: https://t.me/+lVKtdaI5vcQ1ZDA1

📌 How to Build a Neural Machine Translation System for a Low-Resource Language 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-0
📌 How to Build a Neural Machine Translation System for a Low-Resource Language 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-01-24 | ⏱️ Read time: 15 min read An introduction to neural machine translation #DataScience #AI #Python

📌 From Transactions to Trends: Predict When a Customer Is About to Stop Buying 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-23
📌 From Transactions to Trends: Predict When a Customer Is About to Stop Buying 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-23 | ⏱️ Read time: 7 min read Customer churn is usually a gradual process, not a sudden event. In this post, we… #DataScience #AI #Python

📌 Why the Sophistication of Your Prompt Correlates Almost Perfectly with the Sophistication of the Response, as Research by
📌 Why the Sophistication of Your Prompt Correlates Almost Perfectly with the Sophistication of the Response, as Research by Anthropic Found 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-23 | ⏱️ Read time: 9 min read How prompt engineering has evolved, examined scientifically; and implications for the future of conversational AI… #DataScience #AI #Python

📌 Achieving 5x Agentic Coding Performance with Few-Shot Prompting 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-23 | ⏱
📌 Achieving 5x Agentic Coding Performance with Few-Shot Prompting 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-23 | ⏱️ Read time: 9 min read Learn to leverage few-shot prompting to increase your LLMs performance #DataScience #AI #Python