Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost (10.2021)

磁力链接/BT种子名称

Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost (10.2021)

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种子哈希：89ba558fe6f90c78e05a76f711343a3090c3b57c
文件大小： 1.37G
已经下载：2次
下载速度：极快
收录时间：2025-07-06
最近下载：2025-07-07

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文件列表

  • 07 - Setting Up Your Environment (FAQ by Student Request)/001 Anaconda Environment Setup.mp4 176.2 MB
  • 02 - Bias-Variance Trade-Off/004 Polynomial Regression Demo.mp4 150.1 MB
  • 07 - Setting Up Your Environment (FAQ by Student Request)/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 114.6 MB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 85.2 MB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.3 MB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.mp4 67.4 MB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).mp4 58.8 MB
  • 01 - Get Started/002 Where to get the Code and Data.mp4 54.2 MB
  • 04 - Random Forest/002 Random Forest Regressor.mp4 50.4 MB
  • 01 - Get Started/005 How to Succeed in This Course.mp4 46.0 MB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts_ Academic or Practical_ Fast or slow-paced_.mp4 44.5 MB
  • 10 - Appendix _ FAQ Finale/002 BONUS.mp4 37.5 MB
  • 04 - Random Forest/003 Random Forest Classifier.mp4 34.9 MB
  • 01 - Get Started/001 Outline and Motivation.mp4 34.0 MB
  • 03 - Bootstrap Estimates and Bagging/001 Bootstrap Estimation.mp4 31.1 MB
  • 05 - AdaBoost/004 AdaBoost Implementation.mp4 30.4 MB
  • 03 - Bootstrap Estimates and Bagging/005 Bagging Classification Trees.mp4 29.8 MB
  • 05 - AdaBoost/003 AdaBoost Loss Function_ Exponential Loss.mp4 24.5 MB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).mp4 21.9 MB
  • 06 - Background Review/001 Confidence Intervals.mp4 21.8 MB
  • 04 - Random Forest/001 Random Forest Algorithm.mp4 21.6 MB
  • 02 - Bias-Variance Trade-Off/005 K-Nearest Neighbor and Decision Tree Demo.mp4 21.0 MB
  • 03 - Bootstrap Estimates and Bagging/004 Bagging Regression Trees.mp4 19.5 MB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).mp4 18.7 MB
  • 05 - AdaBoost/001 AdaBoost Algorithm.mp4 17.2 MB
  • 02 - Bias-Variance Trade-Off/001 Bias-Variance Key Terms.mp4 15.6 MB
  • 04 - Random Forest/005 Implementing a _Not as Random_ Forest.mp4 14.5 MB
  • 03 - Bootstrap Estimates and Bagging/002 Bootstrap Demo.mp4 13.4 MB
  • 02 - Bias-Variance Trade-Off/007 Suggestion Box.mp4 12.4 MB
  • 01 - Get Started/004 Plug-and-Play.mp4 10.2 MB
  • 04 - Random Forest/004 Random Forest vs Bagging Trees.mp4 10.2 MB
  • 05 - AdaBoost/007 Summary and What's Next.mp4 10.1 MB
  • 02 - Bias-Variance Trade-Off/006 Cross-Validation as a Method for Optimizing Model Complexity.mp4 9.8 MB
  • 05 - AdaBoost/006 Connection to Deep Learning.mp4 9.6 MB
  • 03 - Bootstrap Estimates and Bagging/006 Stacking.mp4 9.3 MB
  • 03 - Bootstrap Estimates and Bagging/003 Bagging.mp4 9.1 MB
  • 01 - Get Started/003 All Data is the Same.mp4 8.4 MB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.mp4 8.0 MB
  • 05 - AdaBoost/005 Comparison to Stacking.mp4 7.9 MB
  • 02 - Bias-Variance Trade-Off/002 Bias-Variance Trade-Off.mp4 6.5 MB
  • 10 - Appendix _ FAQ Finale/001 What is the Appendix_.mp4 6.4 MB
  • 04 - Random Forest/006 Connection to Deep Learning_ Dropout.mp4 5.8 MB
  • 02 - Bias-Variance Trade-Off/003 Bias-Variance Decomposition.mp4 5.5 MB
  • 05 - AdaBoost/002 Additive Modeling.mp4 3.6 MB
  • 01 - Get Started/2021 Software - Windows - Office - Adobe.pdf 231.2 kB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/002 Is this for Beginners or Experts_ Academic or Practical_ Fast or slow-paced_.vtt 28.4 kB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/004 Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 20.7 kB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/001 How to Code by Yourself (part 1).vtt 20.3 kB
  • 07 - Setting Up Your Environment (FAQ by Student Request)/001 Anaconda Environment Setup.vtt 17.8 kB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/003 Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 14.4 kB
  • 09 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/001 How to Succeed in this Course (Long Version).vtt 13.2 kB
  • 07 - Setting Up Your Environment (FAQ by Student Request)/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.7 kB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/003 Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/002 How to Code by Yourself (part 2).vtt 11.9 kB
  • 01 - Get Started/002 Where to get the Code and Data.vtt 11.9 kB
  • 06 - Background Review/001 Confidence Intervals.vtt 11.8 kB
  • 02 - Bias-Variance Trade-Off/004 Polynomial Regression Demo.vtt 11.7 kB
  • 03 - Bootstrap Estimates and Bagging/001 Bootstrap Estimation.vtt 11.3 kB
  • 04 - Random Forest/001 Random Forest Algorithm.vtt 11.0 kB
  • 05 - AdaBoost/004 AdaBoost Implementation.vtt 9.8 kB
  • 05 - AdaBoost/001 AdaBoost Algorithm.vtt 8.2 kB
  • 02 - Bias-Variance Trade-Off/001 Bias-Variance Key Terms.vtt 8.0 kB
  • 04 - Random Forest/002 Random Forest Regressor.vtt 7.6 kB
  • 05 - AdaBoost/003 AdaBoost Loss Function_ Exponential Loss.vtt 7.6 kB
  • 01 - Get Started/005 How to Succeed in This Course.vtt 7.5 kB
  • 01 - Get Started/001 Outline and Motivation.vtt 7.2 kB
  • 10 - Appendix _ FAQ Finale/002 BONUS.vtt 7.1 kB
  • 05 - AdaBoost/007 Summary and What's Next.vtt 5.6 kB
  • 08 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/004 Python 2 vs Python 3.vtt 5.5 kB
  • 02 - Bias-Variance Trade-Off/006 Cross-Validation as a Method for Optimizing Model Complexity.vtt 5.2 kB
  • 02 - Bias-Variance Trade-Off/005 K-Nearest Neighbor and Decision Tree Demo.vtt 5.2 kB
  • 04 - Random Forest/003 Random Forest Classifier.vtt 5.1 kB
  • 03 - Bootstrap Estimates and Bagging/005 Bagging Classification Trees.vtt 4.9 kB
  • 03 - Bootstrap Estimates and Bagging/006 Stacking.vtt 4.6 kB
  • 04 - Random Forest/005 Implementing a _Not as Random_ Forest.vtt 4.5 kB
  • 05 - AdaBoost/006 Connection to Deep Learning.vtt 4.3 kB
  • 02 - Bias-Variance Trade-Off/007 Suggestion Box.vtt 4.2 kB
  • 03 - Bootstrap Estimates and Bagging/004 Bagging Regression Trees.vtt 4.1 kB
  • 01 - Get Started/003 All Data is the Same.vtt 4.0 kB
  • 04 - Random Forest/004 Random Forest vs Bagging Trees.vtt 4.0 kB
  • 05 - AdaBoost/005 Comparison to Stacking.vtt 3.9 kB
  • 03 - Bootstrap Estimates and Bagging/002 Bootstrap Demo.vtt 3.7 kB
  • 02 - Bias-Variance Trade-Off/002 Bias-Variance Trade-Off.vtt 3.7 kB
  • 02 - Bias-Variance Trade-Off/003 Bias-Variance Decomposition.vtt 3.4 kB
  • 10 - Appendix _ FAQ Finale/001 What is the Appendix_.vtt 3.4 kB
  • 04 - Random Forest/006 Connection to Deep Learning_ Dropout.vtt 2.9 kB
  • 03 - Bootstrap Estimates and Bagging/003 Bagging.vtt 2.8 kB
  • 01 - Get Started/004 Plug-and-Play.vtt 2.6 kB
  • 05 - AdaBoost/002 Additive Modeling.vtt 2.1 kB
  • 01 - Get Started/external-assets-links.txt 76 Bytes

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