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 40 149 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 375-o'rinni va Suriya mintaqasida 227-o'rinni egallagan.

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невідомо sanasidan buyon loyiha tez o‘sib, 40 149 obunachiga ega bo‘ldi.

28 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 378 ga, so‘nggi 24 soatda esa 7 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 2.09% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.91% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 841 marta ko‘riladi; birinchi sutkada odatda 766 ta ko‘rish yig‘iladi.
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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 29 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.

40 149

Obunachilar

+724 soatlar

+1147 kunlar

+37830 kunlar

841

Post ko'rishlar

~ 76624 soatlar

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2.09%

Muloqot nisbati

~ 3

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Postlar arxiv

40 147

📌 A New Method to Detect “Confabulations” Hallucinated by Large Language Models 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-25 | ⏱️ Read time: 12 min read By calculating semantic entropy with a second LLM, we can better flag answers as unreliable…

40 147

📌 Making LLMs Write Better and Better Code for Self-Driving Using LangProp 🗂 Category: CHATGPT 🕒 Date: 2024-06-25 | ⏱️ Read time: 11 min read Analogy from classical machine learning: LLM (Large Language Model) = optimizer; code = parameters; LangProp…

40 147

📌 Improving RAG Performance Using Rerankers 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-25 | ⏱️ Read time: 11 min read A tutorial on using rerankers to improve your RAG pipeline

40 147

📌 The Intuitive Basics of Optimization 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-26 | ⏱️ Read time: 14 min read A gentle introduction to the amazing field of optimization

40 147

📌 Business Planning with Python – Revenue Optimization 🗂 Category: BUSINESS 🕒 Date: 2024-06-26 | ⏱️ Read time: 14 min read How can you use data analytics to help small businesses maximize their revenue while maintaining…

40 147

📌 How Bend Works: A Parallel Programming Language That “Feels Like Python but Scales Like CUDA” 🗂 Category: 🕒 Date: 2024-06-26 | ⏱️ Read time: 26 min read A brief introduction to Lambda Calculus, Interaction Combinators, and how they are used to parallelize…

40 147

📌 The Ultimate Guide to Finding Outliers in Your Time-Series Data (Part 2) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-26 | ⏱️ Read time: 1 min read Effective machine learning methods and tools for outlier detection in time-series analysis

40 147

📌 A Complete Guide to Master Step Functions on AWS 🗂 Category: SCIENCE AND TECHNOLOGY 🕒 Date: 2024-06-27 | ⏱️ Read time: 10 min read Workflow orchestration made easier

40 147

📌 3 Challenges to Being a Data Scientist in 2024 🗂 Category: CAREER ADVICE 🕒 Date: 2024-06-27 | ⏱️ Read time: 7 min read Given the current climate, is data science for you?

40 147

📌 Classification Loss Functions: Intuition and Applications 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-27 | ⏱️ Read time: 9 min read A simpler way to understand derivations of loss functions for classification and when/how to apply…

40 147

📌 Prompt Engineering: Tips, Approaches, and Future Directions 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-27 | ⏱️ Read time: 5 min read Our weekly selection of must-read Editors’ Picks and original features

40 147

📌 Understanding Transformers 🗂 Category: DEEP LEARNING 🕒 Date: 2024-06-27 | ⏱️ Read time: 12 min read A straightforward breakdown of “Attention is All You Need”¹

40 147

📌 I Invented a Way to Speak to an AI, Keeping Your Privacy 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 9 min read The tech is called “Silent Voice.”

40 147

📌 The Math Behind Risk – Part 1 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 11 min read Does the attack really have an advantage in the game of world conquest?

40 147

📌 The History of Convolutional Neural Networks for Image Classification (1989- Today) 🗂 Category: DEEP LEARNING 🕒 Date: 2024-06-28 | ⏱️ Read time: 18 min read A tour through the history of Computer Vision!

40 147

📌 Safeguarding Demand Forecasting with Causal Graphs 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 11 min read Causal AI, exploring the integration of causal reasoning into machine learning

40 147

📌 Diving Deep into AutoGen and Agentic Frameworks 🗂 Category: 🕒 Date: 2024-06-28 | ⏱️ Read time: 13 min read This blog post will go into the details of the “AutoGen: Enabling Next-Gen LLM Applications…

40 147

📌 Estimate the unobserved – Moving-Average Model Estimation with Maximum Likelihood in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 8 min read How unobserved covariates’ coefficients can be estimated with MLE

40 147

📌 CRAG – Intuitively and Exhaustively Explained 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-28 | ⏱️ Read time: 13 min read Defining the Limits of Retrieval Augmented Generation

40 147

📌 System Design: Load Balancer 🗂 Category: 🕒 Date: 2024-06-28 | ⏱️ Read time: 9 min read Orchestrating strategies for optimal workload distribution in microservice applications