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

Red:Machine Learning with Python Siria232 Tecnologías y Aplicaciones3 406...

📈 Análisis del canal de Telegram Machine Learning

El canal Machine Learning (@machinelearning9) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 039 suscriptores, ocupando la posición 3 406 en la categoría Tecnologías y Aplicaciones y el puesto 232 en la región Siria.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 039 suscriptores.

Según los últimos datos del 21 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 398, y en las últimas 24 horas de -1, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.30%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.15% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 920 visualizaciones. En el primer día suele acumular 461 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
Intereses temáticos: El contenido se centra en temas clave como distance, insidead, gpu, learning, degree.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 22 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

40 039

Suscriptores

-124 horas

+467 días

+39830 días

920

Visitas de la publicación

~ 46124 horas

~ 62248 horas

2.30%

Tasa de compromiso

~ 3

Mensajes por día

Ads index

beta

Archivo de publicaciones

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📌 How to Get Hired in the AI Era 🗂 Category: CAREER ADVICE 🕒 Date: 2026-05-01 | ⏱️ Read time: 7 min read What people actually look for when hiring juniors that stand out. #DataScience #AI #Python

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🧮 $40/day × 30 days = $1,200/month. That's what my students average. From their phone. In 10 minutes a day. No degree needed. No investment knowledge required. Just Copy & Paste my moves. I'm Tania, and this is real. 👉 Join for Free, Click here #ad 📢 InsideAd

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Leaked 7‑minute pre‑trade checklist: I stole this after watching 12 losing trades in a row… and it flipped my next 3 sessions. 1) mark the 2 liquidity levels first, 2) wait for the 15m sweep, 3) confirm 1 candle shift, 4) set 1R auto‑rule, 5) log the screenshot before entry. Want the template? Join Checklist #ad 📢 InsideAd

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Repost from Machine Learning with Python

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📌 Why AI Engineers Are Moving Beyond LangChain to Native Agent Architectures 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-30 | ⏱️ Read time: 8 min read Frameworks accelerated the first wave of LLM apps, but production demands a different architecture. #DataScience #AI #Python

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📌 How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-30 | ⏱️ Read time: 10 min read How can you validate that your variables tell a consistent risk? #DataScience #AI #Python

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📌 Proxy-Pointer RAG: Multimodal Answers Without Multimodal Embeddings 🗂 Category: LARGE LANGUAGE MODEL 🕒 Date: 2026-04-30 | ⏱️ Read time: 15 min read Structure is all you need #DataScience #AI #Python

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📌 A Gentle Introduction to Stochastic Programming 🗂 Category: MATHEMATICS 🕒 Date: 2026-04-30 | ⏱️ Read time: 15 min read How to make decisions when your spreadsheet is lying about the future #DataScience #AI #Python

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📌 4 YAML Files Instead of PySpark: How We Let Analysts Build Data Pipelines Without Engineers 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-04-29 | ⏱️ Read time: 10 min read How we replaced Python pipelines with dlt, dbt, and Trino — and cut delivery time… #DataScience #AI #Python

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How a University Student Built a Game Changing Bot for Polymarket – And You Can Use It Too A computer science student built a bot that snipes trades before the market reacts! Meet Peter, who automated crypto trading by tracking blockchain data delays. He created the Oracle Lag Sniper to get in on Polymarket trades faster than anyone else. ⚡ Why it works: • Super Fast Execution: Snipes trades before the market catches up • Polymarket-Optimized: Built for speed & accuracy • Open Source & Free: Tweak it as you wish • Easy Setup: No tech skills required! Start using the Oracle Lag Sniper today. Head to GitHub, set it up, and make smarter, quicker trades. Sponsored by Polymarket Analytics

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📌 System Design Series: Apache Flink from 10,000 Feet, and Building a Flink-powered Recommendation Engine 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-29 | ⏱️ Read time: 17 min read A deep dive into how Apache Flink works, why it exists, and learning it while… #DataScience #AI #Python

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In the last 14 days, 63% of retail trades were stopped out… but not because the market “hates” you - it’s the plan that’s missing. 𝗘𝗟𝗜𝗧𝗘𝗣𝗜𝗣 𝗘𝗠𝗣𝗜𝗥𝗘 helps you trade calmer with daily setups, clear levels, and 1-on-1 support when you feel stuck. Less panic. More structure. Request access here: Join #ad 📢 InsideAd

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📌 Agentic AI: How to Save on Tokens 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-29 | ⏱️ Read time: 26 min read Caching, lazy-loading, routing, compaction, and more #DataScience #AI #Python

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📌 Ensembles of Ensembles of Ensembles: A Guide to Stacking 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-04-29 | ⏱️ Read time: 9 min read The best machine learning model is not one model #DataScience #AI #Python

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📌 Correlation Doesn’t Mean Causation! But What Does It Mean? 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-28 | ⏱️ Read time: 6 min read What does correlation tells us? #DataScience #AI #Python

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📌 Let the AI Do the Experimenting 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-28 | ⏱️ Read time: 14 min read Using autoresearch to optimise marketing campaigns under budget constraints #DataScience #AI #Python

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I watched 3 traders blow accounts in 7 days… for the same 1 mistake. Here’s the fix. Leaked Checklist (ELITEPIP EMPIRE): - Spot the 2 news traps that fake out “easy” entries - Use the 3-step setup filter to skip low-quality signals - Lock risk with a 1-minute position plan - Read market bias in under 5 minutes Join & level up | Get access #ad 📢 InsideAd

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📌 PyTorch NaNs Are Silent Killers — So I Built a 3ms Hook to Catch Them at the Exact Layer 🗂 Category: DEEP LEARNING 🕒 Date: 2026-04-28 | ⏱️ Read time: 11 min read NaNs don’t crash your training — they quietly destroy it. After losing hours to a… #DataScience #AI #Python

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Most AAU econ students spend hours struggling with materials, not knowing the hidden cost: relying only on lecture notes limits your exam success. Unlock stress-free preparation with our complete, verified materials, past exams, and reference books-all in one place. Study smarter, stay confident, and ace the future! Join us now 👉 AAU ECONOMICS STUDENT2018 #ad 📢 InsideAd

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📌 The Next Frontier of AI in Production Is Chaos Engineering 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-04-28 | ⏱️ Read time: 18 min read Blast-radius control tells you how much to break. Intent tells you what breaking it will… #DataScience #AI #Python