[FreeCoursesOnline.Me] [Packt] Python Machine Learning Tips, Tricks, and Techniques [FCO]

磁力链接/BT种子名称

[FreeCoursesOnline.Me] [Packt] Python Machine Learning Tips, Tricks, and Techniques [FCO]

磁力链接/BT种子简介

种子哈希：d59ed3c39c48169d04a9a9874a49986c44794683
文件大小：758.37M
已经下载：851次
下载速度：极快
收录时间：2021-03-19
最近下载：2024-11-28

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文件列表

  • 24 - Perform Metric Selection on Real Data.mp4 230.9 MB
  • 02 - Using Feature Scaling to Standardize Data.mp4 39.3 MB
  • 08 - Implementing kNN on the Data Set.mp4 35.9 MB
  • 13 - Gradient Boosting Trees and Bayes Optimization.mp4 35.0 MB
  • 16 - Implement Stacking.mp4 32.7 MB
  • 19 - Applying Matrix Factorization on Datasets.mp4 28.8 MB
  • 15 - Implement Blending.mp4 28.7 MB
  • 09 - Decision Tree as Predictive Model.mp4 28.4 MB
  • 01 - The Course Overview.mp4 28.3 MB
  • 12 - Random Forest for Classification.mp4 25.0 MB
  • 07 - Support Vector Machines.mp4 24.4 MB
  • 20 - Wordbatch for Real-World Problem.mp4 24.4 MB
  • 21 - Validation Dataset Tuning.mp4 23.2 MB
  • 04 - Extracting Data with Feature Selection and Interaction.mp4 23.0 MB
  • 17 - Memory-Based Collaborative Filtering.mp4 22.4 MB
  • 11 - Combining All Together.mp4 22.3 MB
  • 18 - Item-to-Item Recommendation with kNN.mp4 22.3 MB
  • 10 - Tricks with Dimensionality Reduction.mp4 21.5 MB
  • 14 - CatBoost to Handle Categorical Data.mp4 21.1 MB
  • 23 - Adversarial Validation.mp4 20.9 MB
  • 22 - Regularizing Model to Avoid Overfitting.mp4 15.3 MB
  • 06 - Build Model Based on Real-World Problems.mp4 15.3 MB
  • 05 - Combining All Together.mp4 13.7 MB
  • 03 - Implementing Feature Engineering with Logistic Regression.mp4 12.2 MB
  • 24 - Perform Metric Selection on Real Data.en.ttml 29.3 kB
  • 13 - Gradient Boosting Trees and Bayes Optimization.en.ttml 18.3 kB
  • 19 - Applying Matrix Factorization on Datasets.en.ttml 15.6 kB
  • 15 - Implement Blending.en.ttml 15.3 kB
  • 16 - Implement Stacking.en.ttml 13.9 kB
  • 18 - Item-to-Item Recommendation with kNN.en.ttml 12.8 kB
  • 17 - Memory-Based Collaborative Filtering.en.ttml 12.6 kB
  • 21 - Validation Dataset Tuning.en.ttml 11.1 kB
  • 14 - CatBoost to Handle Categorical Data.en.ttml 10.7 kB
  • 23 - Adversarial Validation.en.ttml 10.0 kB
  • 20 - Wordbatch for Real-World Problem.en.ttml 9.9 kB
  • 22 - Regularizing Model to Avoid Overfitting.en.ttml 8.8 kB
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