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Machine Learning

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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📈 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

📊 受众指标与增长动态

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
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+37230
帖子存档
Listen - 72% of verified reports we tracked this month changed the battlefield map in under 48 hours. Want that kind of clari
Listen - 72% of verified reports we tracked this month changed the battlefield map in under 48 hours. Want that kind of clarity on Sudan, DRC, the Sahel? Forgotten Fronts digs through OSINT, tags confidence, and shows sources so you know what’s real and what’s chatter. Check this out: follow for daily dispatches, rapid alerts, and verified threads. High-signal, no noise. Join us: Forgotten Fronts - or ping @ForgottenFronts_bot for instant alerts. #ad 📢 InsideAd

Tired of watching trades at 2am? Mr Pastore EA made $50→$699 in <1h-safe, stress‑free auto trading. Start from $100: DM #a
Tired of watching trades at 2am? Mr Pastore EA made $50→$699 in <1h-safe, stress‑free auto trading. Start from $100: DM #ad 📢 InsideAd

📌 Lasso Regression: Why the Solution Lives on a Diamond 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-04-23 | ⏱️ Read time: 24
📌 Lasso Regression: Why the Solution Lives on a Diamond 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-04-23 | ⏱️ Read time: 24 min read It’s simpler than you think. #DataScience #AI #Python

📌 Your Synthetic Data Passed Every Test and Still Broke Your Model 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-23 | ⏱️ Read t
📌 Your Synthetic Data Passed Every Test and Still Broke Your Model 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-23 | ⏱️ Read time: 11 min read The silent gaps in synthetic data that only show up when your model is already… #DataScience #AI #Python

🧮 $40/day × 30 days = $1,200/month. That's what my students average. From their phone. In 10 minutes a day. No degree needed
🧮 $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

📌 I Simulated an International Supply Chain and Let OpenClaw Monitor It 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-23 | ⏱️ Rea
📌 I Simulated an International Supply Chain and Let OpenClaw Monitor It 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-23 | ⏱️ Read time: 9 min read Mario asked me why 18% of his shipments were late when every team hit their… #DataScience #AI #Python

A trusted platform for cryptocurrency enthusiasts and reliable trading.

📌 Using a Local LLM as a Zero-Shot Classifier 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-04-23 | ⏱️ Read time: 8 min r
📌 Using a Local LLM as a Zero-Shot Classifier 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-04-23 | ⏱️ Read time: 8 min read A practical pipeline for classifying messy free-text data into meaningful categories using a locally hosted… #DataScience #AI #Python

📌 How to Run OpenClaw with Open-Source Models 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-04-22 | ⏱️ Read time: 8 min r
📌 How to Run OpenClaw with Open-Source Models 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-04-22 | ⏱️ Read time: 8 min read Run OpenClaw assistant through alternative LLMs #DataScience #AI #Python

Today, the public mint for Lobsters on TON goes live on Getgems 🦞 This is not just another NFT drop. In my view, Lobsters is
Today, the public mint for Lobsters on TON goes live on Getgems 🦞 This is not just another NFT drop. In my view, Lobsters is one of the first truly cohesive products at the intersection of blockchain, NFTs, and AI. Here, the NFT is not just an image and not just a collectible. Each Lobster is an NFT with a built-in AI agent inside: a digital character with its own soul, on-chain biography, persistent memory, and a unified identity across Telegram, Mini App, Claude, and API. So you are not just getting an asset in your wallet. You are getting an AI-native digital character that can interact, remember, and stay consistent across different interfaces. What makes this especially interesting is the timing. In the recent video Pavel Durov shared in his post about agentic bots in Telegram, the lobster imagery was right there. Against that backdrop, Lobsters does not feel like a random mint — it feels like a very precise fit for the new narrative: Telegram-native agents + TON infrastructure + NFT ownership layer + AI utility Put simply, this is one of the first real attempts to turn an NFT from “just an image” into a digital agent. Public mint: today, 16:00 Price: 50 TON 👉 Mint your Lobster on Getgems 🦞🦞🦞

📌 Ivory Tower Notes: The Methodology 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-22 | ⏱️ Read time: 6 min read A short intro
📌 Ivory Tower Notes: The Methodology 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-22 | ⏱️ Read time: 6 min read A short intro to scientific methodology to combat “prompt in, slop out” #DataScience #AI #Python

📌 From Ad Hoc Prompting to Repeatable AI Workflows with Claude Code Skills 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-22 | ⏱️
📌 From Ad Hoc Prompting to Repeatable AI Workflows with Claude Code Skills 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-22 | ⏱️ Read time: 8 min read How I turned LLM persona interviews into a repeatable customer research workflow #DataScience #AI #Python

🧮 $40/day × 30 days = $1,200/month. That's what my students average. From their phone. In 10 minutes a day. No degree needed
🧮 $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

11 Plots Data Scientists Use 90% of the Time 📊🚀 Here’s the secret → Data scientists don’t actually use 100+ types of charts. 🤫 When real decisions are on the line, it always comes back to the same 11. https://t.me/DataScienceM

📌 Correlation vs. Causation: Measuring True Impact with Propensity Score Matching 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04
📌 Correlation vs. Causation: Measuring True Impact with Propensity Score Matching 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-22 | ⏱️ Read time: 12 min read Learn how Propensity Score Matching uncovers true causality in observational data. By finding “statistical twins,”… #DataScience #AI #Python

📌 Using Causal Inference to Estimate the Impact of Tube Strikes on Cycling Usage in London 🗂 Category: DATA SCIENCE 🕒 Date
📌 Using Causal Inference to Estimate the Impact of Tube Strikes on Cycling Usage in London 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-22 | ⏱️ Read time: 19 min read Turning free-to-use data into a hypothesis-ready dataset #DataScience #AI #Python

📌 Your RAG Gets Confidently Wrong as Memory Grows – I Built the Memory Layer That Stops It 🗂 Category: LARGE LANGUAGE MODEL
📌 Your RAG Gets Confidently Wrong as Memory Grows – I Built the Memory Layer That Stops It 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-04-21 | ⏱️ Read time: 15 min read As memory grows in RAG systems, accuracy quietly drops while confidence rises — creating a… #DataScience #AI #Python

🧮 $40/day × 30 days = $1,200/month. That's what my students average. From their phone. In 10 minutes a day. No degree needed
🧮 $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

📌 I Replaced GPT-4 with a Local SLM and My CI/CD Pipeline Stopped Failing 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-04-21
📌 I Replaced GPT-4 with a Local SLM and My CI/CD Pipeline Stopped Failing 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-04-21 | ⏱️ Read time: 13 min read The hidden cost of probabilistic outputs in systems that demand reliability #DataScience #AI #Python

🔥 Google Colab has added the option of retraining 500+ open-source neural networks Unsloth has released a convenient notebook for configuring models. Instructions: 1. Open the page in Colab: https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb 2. Run the blocks and the Unsloth Studio itself. 3. Select a model and a dataset. 4. Click "Start Training" and monitor the progress in real time. 5. Everything is ready - you can immediately compare the regular and fine-tuned versions of the model in the chat.