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Machine learning books and papers

Machine learning books and papers

前往频道在 Telegram

📈 Telegram 频道 Machine learning books and papers 的分析概览

频道 Machine learning books and papers (@machine_learn) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 24 509 名订阅者,在 教育 类别中位列第 8 019,并在 伊朗 地区排名第 13 748

📊 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 24 509 名订阅者。

根据 04 七月, 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 -101,过去 24 小时变化为 3,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 6.50%。内容发布后 24 小时内通常能获得 2.21% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 1 594 次浏览,首日通常累积 541 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2
  • 主题关注点: 内容集中在 disorder, psy, مقاله, framework, graph 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:
Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn

凭借高频更新(最新数据采集于 05 七月, 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。

24 509
订阅者
+324 小时
-97
-10130
帖子存档
Understanding Machine Learning from Theory to Algorithms – Shai Shalev-Shwartz, Shai Ben-David (en) 2014 #book #junior #theor
Understanding Machine Learning from Theory to Algorithms – Shai Shalev-Shwartz, Shai Ben-David (en) 2014 #book #junior #theory @Machine_learn

Gaussian Processes for Machine Learning – C. E. Rasmussen, Christopher K. I. Williams (en) 2006 #book #middle #theory @Machine_learn

Gaussian Processes for Machine Learning – C. E. Rasmussen, Christopher K. I. Williams (en) 2006 #book #middle #theory @Machin
Gaussian Processes for Machine Learning – C. E. Rasmussen, Christopher K. I. Williams (en) 2006 #book #middle #theory @Machine_learn

Advanced Analytics with Spark — S. Ryza и др. (en) 2017 #book #middle #spark @Machine_learn

Advanced Analytics with Spark — S. Ryza и др. (en) 2017 #book #middle #spark @Machine_learn
Advanced Analytics with Spark — S. Ryza и др. (en) 2017 #book #middle #spark @Machine_learn

#Alice_Zheng_Feature_Engineering_for_Machine_Learning_2018 #book @Machine_learn

#Alice_Zheng_Feature_Engineering_for_Machine_Learning_2018 #book @Machine_learn
#Alice_Zheng_Feature_Engineering_for_Machine_Learning_2018 #book @Machine_learn

discriminative : 1:#Regression 2:#Logistic regression 3:#decision tree(Hunt) 4:#neural network(traditional network, deep network) 5:#Support Vector Machine(SVM) Generative: 1:#Hidden Markov model 2:#Naive bayes 3:#K-nearest neighbor(KNN) 4:#Generative adversarial networks(GANs) Deep learning: 1:CNN 2:RNN 3:LSTM 4:CapsuleNet 5:Siamese: siamese cnn siamese lstm siamese bi-lstm siamese CapsuleNet 6:time series data درخواست پیاده سازی @RaminMousa

Machine Learning Refined — J. Watt, R. Borhani, A. K. Katsaggelos (en) 2016 #book #middle #theory @Machine_learn

Machine Learning Refined — J. Watt, R. Borhani, A. K. Katsaggelos (en) 2016 #book #middle #theory @Machine_learn
Machine Learning Refined — J. Watt, R. Borhani, A. K. Katsaggelos (en) 2016 #book #middle #theory @Machine_learn

Applied Text Analysis with Python — B. Bengfort, R. Bilbro, T. Ojeda (en) 2016 #book #middle #python @Machine_learn

Applied Text Analysis with Python — B. Bengfort, R. Bilbro, T. Ojeda (en) 2016 #book #middle #python @Machine_learn
Applied Text Analysis with Python — B. Bengfort, R. Bilbro, T. Ojeda (en) 2016 #book #middle #python @Machine_learn

Practical Machine Learning – Sunila Gollapudi (en) #book #middle #theory @Machine_learn

Practical Machine Learning – Sunila Gollapudi (en) #book #middle #theory @Machine_learn
Practical Machine Learning – Sunila Gollapudi (en) #book #middle #theory @Machine_learn

#Marcos Lopez de Prado-Advances in Financial Machine Learning-Wiley #2018 #book @Machine_learn

#Biostatistical modeling Frank Harrel #note @Machine_learn

#Biostatistical modeling Frank Harrel #note @Machine_learn
#Biostatistical modeling Frank Harrel #note @Machine_learn

🔴 OpenCV Computer Vision with Python بینایی ماشین با پایتون و opencv @Machine_learn

@CVision اخبار حوزه یادگیری عمیق و هوش مصنوعی مقالات و یافته های جدید یادگیری عمیق آموزشهای مرتبط با تنسرفلو و کراس بینایی ما
@CVision اخبار حوزه یادگیری عمیق و هوش مصنوعی مقالات و یافته های جدید یادگیری عمیق آموزشهای مرتبط با تنسرفلو و کراس بینایی ماشین و پردازش تصویر و ... #deep_learning #tensorflow #keras #computer_vision #vision @cvision