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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
Ko'proq ko'rsatish📈 Telegram kanali Machine Learning analitikasi
Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 221 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 344-o'rinni va Suriya mintaqasida 228-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 40 221 obunachiga ega bo‘ldi.
03 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 338 ga, so‘nggi 24 soatda esa 9 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 2.42% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 822 marta ko‘riladi; birinchi sutkada odatda 973 ta ko‘rish yig‘iladi.
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📝 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 04 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.
40 221
Obunachilar
+924 soatlar
+727 kunlar
+33830 kunlar
Postlar arxiv
40 221
📌 Automatic Differentiation (AutoDiff): A Brief Intro with Examples
🗂 Category: DEEP LEARNING
🕒 Date: 2024-10-11 | ⏱️ Read time: 11 min read
An introduction to the mechanics of AutoDiff, exploring its mathematical principles, implementation strategies, and applications
40 221
📌 Topic Alignment for NLP Recommender Systems
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-11 | ⏱️ Read time: 18 min read
Leveraging topic modeling to align user queries with document themes, enhancing the relevance and contextual…
40 221
📌 A Mixed-Methods Approach to Offline Evaluation of News Recommender Systems
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-11 | ⏱️ Read time: 8 min read
Combining reader feedback from surveys with behavioral click data to optimize content personalization.
40 221
📌 Understanding Automatic Differentiation in JAX: A Deep Dive
🗂 Category: DEEP LEARNING
🕒 Date: 2024-10-11 | ⏱️ Read time: 12 min read
Unleashing the Gradient: How JAX Makes Automatic Differentiation Feel Like Magic
40 221
📌 Common Misconceptions About Data Science
🗂 Category: CAREER ADVICE
🕒 Date: 2024-10-11 | ⏱️ Read time: 7 min read
Data science advice that you should question
40 221
📌 Bursting the AI Hype Bubble Once and for All
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-12 | ⏱️ Read time: 11 min read
Misinformation and poor research: a case study
40 221
📌 Gaussian Naive Bayes, Explained: A Visual Guide with Code Examples for Beginners
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-12 | ⏱️ Read time: 8 min read
Bell-shaped assumptions for better predictions
40 221
📌 Improve Your RAG Context Recall by 95% with an Adapted Embedding Model.
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2024-10-12 | ⏱️ Read time: 11 min read
Step by Step Model Adaptation Code and Results Attached.
40 221
📌 Why the 2024 Nobel Prize in (AI for) Chemistry Matters So Much
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-12 | ⏱️ Read time: 6 min read
To Demis Hassabis and John Jumper, from DeepMind, and to David Baker, leader of the…
40 221
📌 Upgrading to Prefect Push Workers on AWS ECS
🗂 Category: DATA ENGINEERING
🕒 Date: 2024-10-12 | ⏱️ Read time: 6 min read
Upgrade from Prefect 2.0 to 3.0 and use the new Push Work Pools that greatly…
40 221
📌 Linear Discriminant Analysis (LDA)
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-10-12 | ⏱️ Read time: 13 min read
Discover how LDA helps identify critical data features
40 221
📌 Top 5 Principles for Building User-Friendly Data Tables
🗂 Category: DATA ENGINEERING
🕒 Date: 2024-10-13 | ⏱️ Read time: 9 min read
Designing intuitive and reliable tables that your data team will love
40 221
📌 Recruiting vs. Interviewing for Data Roles in Diverse Markets
🗂 Category: CAREER ADVICE
🕒 Date: 2024-10-13 | ⏱️ Read time: 12 min read
Factors of success in recruiting and interviewing after applying for 150+ positions and reviewing 500+…
40 221
📌 How to Perform A/B Testing with Hypothesis Testing in Python: A Comprehensive Guide
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-13 | ⏱️ Read time: 11 min read
A Step-by-Step Guide to Making Data-Driven Decisions with Practical Python Examples
40 221
📌 Bringing Structure to Your Data
🗂 Category:
🕒 Date: 2024-10-14 | ⏱️ Read time: 13 min read
Testing assumptions with path models
40 221
📌 lintsampler: a new way to quickly get random samples from any distribution
🗂 Category: PROBABILITY
🕒 Date: 2024-10-14 | ⏱️ Read time: 5 min read
lintsampler is a pure Python package that can easily and efficiently generate random samples from…
40 221
📌 Product-Oriented ML: A Guide for Data Scientists
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-14 | ⏱️ Read time: 30 min read
How to build ML products users love
40 221
📌 How to Set Bid Guardrails in PPC Marketing
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-14 | ⏱️ Read time: 14 min read
Without controls, bidding algorithms can be quite volatile. Learn how to protect performance through adding…
40 221
📌 PyTorch Optimizers Aren’t Fast Enough. Try These Instead
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-14 | ⏱️ Read time: 12 min read
These 4 advanced optimizers will open your mind.
40 221
📌 Florence-2: Advancing Multiple Vision Tasks with a Single VLM Model
🗂 Category:
🕒 Date: 2024-10-14 | ⏱️ Read time: 8 min read
A Guided Exploration of Florence-2’s Zero-Shot Capabilities: Captioning, Object Detection, Segmentation and OCR.
