Machine Learning with Python
前往频道在 Telegram
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
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网络:📈 Telegram 频道 Machine Learning with Python 的分析概览
频道 Machine Learning with Python (@codeprogrammer) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 68 103 名订阅者，在 教育 类别中位列第 2 374，并在 印度 地区排名第 4 765 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 68 103 名订阅者。
根据 28 八月, 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 75，过去 24 小时变化为 -18，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 4.69%。内容发布后 24 小时内通常能获得 1.70% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 3 194 次浏览，首日通常累积 1 155 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 6。
- 主题关注点： 内容集中在 insidead, learning, degree, evaluation, algorithm 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：
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
凭借高频更新（最新数据采集于 29 八月, 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 教育 类别中的关键影响点。
68 103
订阅者
-1824 小时
-907 天
+7530 天
帖子存档
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These Google Colab-notebooks help to implement all machine learning algorithms from scratch 🤯
Repo: https://udlbook.github.io/udlbook/
👉 @codeprogrammer
Repost from Machine Learning
4 learning paradigms in machine learning, explained visually:
1. Transfer Learning
2. Fine-tuning
3. Multi-task Learning
4. Federated Learning
👉 @DataScienceM
🧠 𝐊-𝐍𝐞𝐚𝐫𝐞𝐬𝐭 𝐍𝐞𝐢𝐠𝐡𝐛𝐨𝐫𝐬 (𝐊𝐍𝐍)
🔹 𝐖𝐡𝐚𝐭 𝐈 𝐜𝐨𝐯𝐞𝐫𝐞𝐝 𝐭𝐨𝐝𝐚𝐲
𝐖𝐡𝐚𝐭 𝐊𝐍𝐍 𝐢𝐬 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬
𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐊𝐍𝐍 𝐟𝐨𝐫 𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐯𝐬 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧
𝐑𝐨𝐥𝐞 𝐨𝐟 𝐊 (𝐡𝐲𝐩𝐞𝐫𝐩𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫)
𝐃𝐢𝐬𝐭𝐚𝐧𝐜𝐞 𝐦𝐞𝐭𝐫𝐢𝐜𝐬: 𝐄𝐮𝐜𝐥𝐢𝐝𝐞𝐚𝐧 𝐯𝐬 𝐌𝐚𝐧𝐡𝐚𝐭𝐭𝐚𝐧
𝐖𝐡𝐲 𝐊𝐍𝐍 𝐢𝐬 𝐜𝐚𝐥𝐥𝐞𝐝 𝐚 𝐥𝐚𝐳𝐲 / 𝐢𝐧𝐬𝐭𝐚𝐧𝐜𝐞-𝐛𝐚𝐬𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐞𝐫
🎯 𝐓𝐨𝐩 𝟏𝟎 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 (𝐌𝐮𝐬𝐭-𝐊𝐧𝐨𝐰)
1️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘒-𝘕𝘦𝘢𝘳𝘦𝘴𝘵 𝘕𝘦𝘪𝘨𝘩𝘣𝘰𝘳𝘴 (𝘒𝘕𝘕)?
2️⃣ 𝘞𝘩𝘺 𝘪𝘴 𝘒𝘕𝘕 𝘤𝘢𝘭𝘭𝘦𝘥 𝘢 𝘭𝘢𝘻𝘺 𝘭𝘦𝘢𝘳𝘯𝘪𝘯𝘨 𝘢𝘭𝘨𝘰𝘳𝘪𝘵𝘩𝘮?
3️⃣ 𝘋𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘤𝘦 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘒𝘕𝘕 𝘤𝘭𝘢𝘴𝘴𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘒𝘕𝘕 𝘳𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯?
4️⃣ 𝘏𝘰𝘸 𝘥𝘰 𝘺𝘰𝘶 𝘤𝘩𝘰𝘰𝘴𝘦 𝘵𝘩𝘦 𝘷𝘢𝘭𝘶𝘦 𝘰𝘧 𝘒?
5️⃣ 𝘞𝘩𝘢𝘵 𝘩𝘢𝘱𝘱𝘦𝘯𝘴 𝘸𝘩𝘦𝘯 𝘒 𝘪𝘴 𝘵𝘰𝘰 𝘴𝘮𝘢𝘭𝘭 𝘰𝘳 𝘵𝘰𝘰 𝘭𝘢𝘳𝘨𝘦?
6️⃣ 𝘞𝘩𝘢𝘵 𝘥𝘪𝘴𝘵𝘢𝘯𝘤𝘦 𝘮𝘦𝘵𝘳𝘪𝘤𝘴 𝘢𝘳𝘦 𝘤𝘰𝘮𝘮𝘰𝘯𝘭𝘺 𝘶𝘴𝘦𝘥 𝘪𝘯 𝘒𝘕𝘕?
7️⃣ 𝘞𝘩𝘺 𝘥𝘰𝘦𝘴 𝘒𝘕𝘕 𝘱𝘦𝘳𝘧𝘰𝘳𝘮 𝘱𝘰𝘰𝘳𝘭𝘺 𝘰𝘯 𝘩𝘪𝘨𝘩-𝘥𝘪𝘮𝘦𝘯𝘴𝘪𝘰𝘯𝘢𝘭 𝘥𝘢𝘵𝘢?
8️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘵𝘩𝘦 𝘵𝘪𝘮𝘦 𝘤𝘰𝘮𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘰𝘧 𝘒𝘕𝘕?
9️⃣ 𝘏𝘰𝘸 𝘥𝘰 𝘒𝘋-𝘛𝘳𝘦𝘦 𝘢𝘯𝘥 𝘉𝘢𝘭𝘭-𝘛𝘳𝘦𝘦 𝘪𝘮𝘱𝘳𝘰𝘷𝘦 𝘒𝘕𝘕 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦?
🔟 𝘞𝘩𝘦𝘯 𝘴𝘩𝘰𝘶𝘭𝘥 𝘺𝘰𝘶 𝘢𝘷𝘰𝘪𝘥 𝘶𝘴𝘪𝘯𝘨 #𝘒𝘕𝘕?
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Machine Learning Interview prep
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📈 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧
Why Logistic Regression is not regression
How Sigmoid (Logistic) function works
Binary vs Multiclass Logistic Regression
Decision boundaries and probability interpretation
Where Logistic Regression beats complex models
🎯 𝐓𝐨𝐩 𝟏𝟎 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 (𝐌𝐮𝐬𝐭-𝐊𝐧𝐨𝐰)
1️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘓𝘰𝘨𝘪𝘴𝘵𝘪𝘤 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯?
2️⃣ 𝘞𝘩𝘺 𝘪𝘴 𝘓𝘰𝘨𝘪𝘴𝘵𝘪𝘤 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯 𝘶𝘴𝘦𝘥 𝘧𝘰𝘳 𝘤𝘭𝘢𝘴𝘴𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯, 𝘯𝘰𝘵 𝘳𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯?
3️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘵𝘩𝘦 𝘚𝘪𝘨𝘮𝘰𝘪𝘥 𝘧𝘶𝘯𝘤𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘸𝘩𝘺 𝘪𝘴 𝘪𝘵 𝘯𝘦𝘦𝘥𝘦𝘥?
4️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘓𝘰𝘨 𝘓𝘰𝘴𝘴 / 𝘊𝘳𝘰𝘴𝘴-𝘌𝘯𝘵𝘳𝘰𝘱𝘺 𝘓𝘰𝘴𝘴?
5️⃣ 𝘋𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘤𝘦 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘓𝘰𝘨𝘪𝘴𝘵𝘪𝘤 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯 𝘢𝘯𝘥 𝘓𝘪𝘯𝘦𝘢𝘳 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯?
6️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘢 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯 𝘣𝘰𝘶𝘯𝘥𝘢𝘳𝘺?
7️⃣ 𝘏𝘰𝘸 𝘥𝘰𝘦𝘴 𝘙𝘦𝘨𝘶𝘭𝘢𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯 (𝘓1 𝘷𝘴 𝘓2) 𝘸𝘰𝘳𝘬 𝘪𝘯 𝘓𝘰𝘨𝘪𝘴𝘵𝘪𝘤 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯?
8️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘖𝘥𝘥𝘴 𝘙𝘢𝘵𝘪𝘰 𝘢𝘯𝘥 𝘩𝘰𝘸 𝘥𝘰 𝘺𝘰𝘶 𝘪𝘯𝘵𝘦𝘳𝘱𝘳𝘦𝘵 𝘤𝘰𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘵𝘴?
9️⃣ 𝘏𝘰𝘸 𝘥𝘰 𝘺𝘰𝘶 𝘩𝘢𝘯𝘥𝘭𝘦 𝘤𝘭𝘢𝘴𝘴 𝘪𝘮𝘣𝘢𝘭𝘢𝘯𝘤𝘦?
🔟 𝘞𝘩𝘦𝘯 𝘴𝘩𝘰𝘶𝘭𝘥 𝘺𝘰𝘶 𝘢𝘷𝘰𝘪𝘥 𝘓𝘰𝘨𝘪𝘴𝘵𝘪𝘤 𝘙𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯?
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Repost from Machine Learning
The single most undervalued fact of linear algebra: matrices are graphs, and graphs are matrices.
Encoding matrices as graphs is a cheat code, making complex behavior simple to study.
https://t.me/DataScienceM
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
📐 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐕𝐞𝐜𝐭𝐨𝐫 𝐌𝐚𝐜𝐡𝐢𝐧𝐞𝐬 (𝐒𝐕𝐌)
🔹 What I covered today
What SVM is and how it works
Concept of hyperplane, margin, and support vectors
Hard margin vs Soft margin
Role of kernel trick
When SVM performs better than other classifiers
🎯 𝐓𝐨𝐩 𝟏𝟎 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 (𝐌𝐮𝐬𝐭-𝐊𝐧𝐨𝐰)
1️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘚𝘶𝘱𝘱𝘰𝘳𝘵 𝘝𝘦𝘤𝘵𝘰𝘳 𝘔𝘢𝘤𝘩𝘪𝘯𝘦 (𝘚𝘝𝘔)?
2️⃣ 𝘞𝘩𝘢𝘵 𝘢𝘳𝘦 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘷𝘦𝘤𝘵𝘰𝘳𝘴?
3️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘢 𝘮𝘢𝘳𝘨𝘪𝘯 𝘪𝘯 𝘚𝘝𝘔?
4️⃣ 𝘋𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘤𝘦 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘩𝘢𝘳𝘥 𝘮𝘢𝘳𝘨𝘪𝘯 𝘢𝘯𝘥 𝘴𝘰𝘧𝘵 𝘮𝘢𝘳𝘨𝘪𝘯?
5️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘵𝘩𝘦 𝘬𝘦𝘳𝘯𝘦𝘭 𝘵𝘳𝘪𝘤𝘬 𝘢𝘯𝘥 𝘸𝘩𝘺 𝘪𝘴 𝘪𝘵 𝘯𝘦𝘦𝘥𝘦𝘥?
6️⃣ 𝘊𝘰𝘮𝘮𝘰𝘯 𝘬𝘦𝘳𝘯𝘦𝘭𝘴 𝘶𝘴𝘦𝘥 𝘪𝘯 𝘚𝘝𝘔 (𝘓𝘪𝘯𝘦𝘢𝘳, 𝘗𝘰𝘭𝘺𝘯𝘰𝘮𝘪𝘢𝘭, 𝘙𝘉𝘍)?
7️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘵𝘩𝘦 𝘳𝘰𝘭𝘦 𝘰𝘧 𝘊 (𝘳𝘦𝘨𝘶𝘭𝘢𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘱𝘢𝘳𝘢𝘮𝘦𝘵𝘦𝘳)?
8️⃣ 𝘞𝘩𝘢𝘵 𝘪𝘴 𝘨𝘢𝘮𝘮𝘢 𝘪𝘯 𝘙𝘉𝘍 𝘬𝘦𝘳𝘯𝘦𝘭?
9️⃣ 𝘊𝘢𝘯 #𝘚𝘝𝘔 𝘣𝘦 𝘶𝘴𝘦𝘥 𝘧𝘰𝘳 𝘳𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯? (𝘚𝘝𝘙)
🔟 𝘞𝘩𝘦𝘯 𝘴𝘩𝘰𝘶𝘭𝘥 𝘺𝘰𝘶 𝘢𝘷𝘰𝘪𝘥 𝘶𝘴𝘪𝘯𝘨 𝘚𝘝𝘔?
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paper simulation 200$
Contact me
https://t.me/m/-nTmpj5vYzNk
200$ to 20k$ SOL Challenge!
As promised, i will do another challenge for those who missed the previous one!
Last one we completed in 6 days, let’s do this one even quicker!
Join my free group Before closing 👇
https://t.me/+DAKLP7eUy9Y3ZjY0
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nature papers: 1400$
Q1 and Q2 papers 900$
Q3 and Q4 papers 500$
Doctoral thesis (complete) 700$
M.S thesis 300$
paper simulation 200$
Contact me
https://t.me/m/-nTmpj5vYzNk
