Machine Learning

前往频道在 Telegram

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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网络:Machine Learning with Python 叙利亚232 技术与应用3 406...

📈 Telegram 频道 Machine Learning 的分析概览

频道 Machine Learning (@machinelearning9) 英语语言赛道中的是活跃参与者。目前社区聚集了 40 040 名订阅者，在 技术与应用 类别中位列第 3 406，并在 叙利亚 地区排名第 232 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 40 040 名订阅者。

根据 22 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 372，过去 24 小时变化为 2，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 1.94%。内容发布后 24 小时内通常能获得 1.16% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 775 次浏览，首日通常累积 466 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 3。
主题关注点： 内容集中在 distance, insidead, gpu, learning, degree 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

凭借高频更新（最新数据采集于 23 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。

40 040

订阅者

+224 小时

+237 天

+37230 天

775

帖子浏览量

~ 46624 小时

~ 62048 小时

1.94%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

40 038

📌 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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📌 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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📌 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