Udemy - Ensemble Machine Learning in Python: Random Forest, AdaBoost

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[DesireCourse.Com] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost 1. Get Started
  • 1. Outline and Motivation.mp4 (7.2 MB)
  • 1. Outline and Motivation.vtt (6.0 KB)
  • 2. Where to get the Code and Data.mp4 (3.4 MB)
  • 2. Where to get the Code and Data.vtt (2.6 KB)
  • 3. All Data is the Same.mp4 (5.3 MB)
  • 3. All Data is the Same.vtt (3.9 KB)
  • 4. Plug-and-Play.mp4 (3.5 MB)
  • 4. Plug-and-Play.vtt (2.6 KB)
2. Bias-Variance Trade-Off
  • 1. Bias-Variance Key Terms.mp4 (10.2 MB)
  • 1. Bias-Variance Key Terms.vtt (7.8 KB)
  • 2. Bias-Variance Trade-Off.mp4 (4.9 MB)
  • 2. Bias-Variance Trade-Off.vtt (3.6 KB)
  • 3. Bias-Variance Decomposition.mp4 (5.4 MB)
  • 3. Bias-Variance Decomposition.vtt (3.5 KB)
  • 4. Polynomial Regression Demo.mp4 (41.8 MB)
  • 4. Polynomial Regression Demo.vtt (11.4 KB)
  • 5. K-Nearest Neighbor and Decision Tree Demo.mp4 (13.9 MB)
  • 5. K-Nearest Neighbor and Decision Tree Demo.vtt (5.1 KB)
  • 6. Cross-Validation as a Method for Optimizing Model Complexity.mp4 (7.0 MB)
  • 6. Cross-Validation as a Method for Optimizing Model Complexity.vtt (5.1 KB)
3. Bootstrap Estimates and Bagging
  • 1. Bootstrap Estimation.mp4 (47.7 MB)
  • 1. Bootstrap Estimation.vtt (11.0 KB)
  • 2. Bootstrap Demo.mp4 (11.0 MB)
  • 2. Bootstrap Demo.vtt (3.6 KB)
  • 3. Bagging.mp4 (3.9 MB)
  • 3. Bagging.vtt (2.7 KB)
  • 4. Bagging Regression Trees.mp4 (15.9 MB)
  • 4. Bagging Regression Trees.vtt (4.0 KB)
  • 5. Bagging Classification Trees.mp4 (20.3 MB)
  • 5. Bagging Classification Trees.vtt (4.8 KB)
  • 6. Stacking.mp4 (6.1 MB)
  • 6. Stacking.vtt (4.5 KB)
4. Random Forest
  • 1. Random Forest Algorithm.mp4 (14.4 MB)
  • 1. Random Forest Algorithm.vtt (10.7 KB)
  • 2. Random Forest Regressor.mp4 (14.9 MB)
  • 2. Random Forest Regressor.vtt (7.5 KB)
  • 3. Random Forest Classifier.mp4 (12.6 MB)
  • 3. Random Forest Classifier.vtt (5.0 KB)
  • 4. Random Forest vs Bagging Trees.mp4 (7.8 MB)
  • 4. Random Forest vs Bagging Trees.vtt (3.9 KB)
  • 5. Implementing a Not as Random Forest.mp4 (8.7 MB)
  • 5. Implementing a Not as Random Forest.vtt (4.4 KB)
  • 6. Connection to Deep Learning Dropout.mp4 (4.2 MB)
  • 6. Connection to Deep Learning Dropout.vtt (2.8 KB)
5. AdaBoost
  • 1. AdaBoost Algorithm.mp4 (10.9 MB)
  • 1. AdaBoost Algorithm.vtt (8.0 KB)
  • 2. Additive Modeling.mp4 (2.8 MB)
  • 2. Additive Modeling.vtt (2.1 KB)
  • 3. AdaBoost Loss Function Exponential Loss.mp4 (11.2 MB)
  • 3. AdaBoost Loss Function Exponential Loss.vtt (7.4 KB)
  • 4. AdaBoost Implementation.mp4 (15.8 MB)
  • 4. AdaBoost Implementation.vtt (9.6 KB)
  • 5. Comparison to Stacking.mp4 (5.5 MB)
  • 5. Comparison to Stacking.vtt (3.8 KB)
  • 6. Connection to Deep Learning.mp4 (6.0 MB)
  • 6. Connection to Deep Learning.vtt (4.2 KB)
  • 7. Summary and What's Next.mp4 (7.4 MB)
  • 7. Summary and What's Next.vtt (5.5 KB)
6. Appendix
  • 1. What is the Appendix.mp4 (5.5 MB)
  • 1. What is the Appendix.vtt (3.3 KB)
  • 10. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 (4.0 MB)
  • 10. BONUS Where to get Udemy coupons and FREE deep learning material.vtt (3.0 KB)
  • 11. Python 2 vs Python 3.mp4 (7.8 MB)
  • 11. Python 2 vs Python 3.vtt (5.4 KB)
  • 12. What order should I take your courses in (part 1).mp4 (29.3 MB)
  • 12. What order should I take your courses in (part 1).vtt (14.1 KB)
  • 13. What order should I take your courses in (part 2).mp4 (37.6 MB)
  • 13. What order should I take your courses in (part 2).vtt (20.2 KB)
  • 2. Confidence Intervals.mp4 (12.6 MB)
  • 2. Confidence Intervals.vtt (11.5 KB)
  • 3. Windows-Focused Environment Setup 2018.mp4 (186.3 MB)
  • 3. Windows-Focused Environment Setup 2018.vtt (17.4 KB)
  • 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
  • 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt (12.4 KB)
  • 5. How to Code by Yourself (part 1).mp4 (24.5 MB)
  • 5. How to Code by Yourself (part 1).vtt (19.8 KB)
  • 6. How to Code by Yourself (part 2).mp4 (14.8 MB)
  • 6. How to Code by Yourself (part 2).vtt (11.6 KB)
  • 7. How to Succeed in this Course (Long Version).mp4 (13.0 MB)
  • 7. How to Succeed in this Course (Long Version).vtt (12.9 KB)
  • 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
  • 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt (27.8 KB)
  • 9. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
  • 9. Proof that using Jupyter Notebook is the same as not using it.vtt (12.2 KB)
  • [DesireCourse.Com].url (0.0 KB)

Description

Ensemble Machine Learning in Python: Random Forest, AdaBoost

Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python

For More Courses Visit: https://desirecourse.com



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Udemy - Ensemble Machine Learning in Python: Random Forest, AdaBoost

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Download torrent
826.3 MB
seeders:7
leechers:3
Udemy - Ensemble Machine Learning in Python: Random Forest, AdaBoost

Torrent hash: C36599619801D7FB84E1C3D652DA4BB26CA9AFCD