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

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Udemy - Ensemble Machine Learning in Python: Random Forest, AdaBoost (Size: 826.3 MB)
  1. AdaBoost Algorithm.mp4 10.9 MB
  1. AdaBoost Algorithm.vtt 8 KB
  1. Bias-Variance Key Terms.mp4 10.2 MB
  1. Bias-Variance Key Terms.vtt 7.8 KB
  1. Bootstrap Estimation.mp4 47.7 MB
  1. Bootstrap Estimation.vtt 11 KB
  1. Outline and Motivation.mp4 7.2 MB
  1. Outline and Motivation.vtt 6 KB
  1. Random Forest Algorithm.mp4 14.4 MB
  1. Random Forest Algorithm.vtt 10.7 KB
  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 MB
  10. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3 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. Additive Modeling.mp4 2.8 MB
  2. Additive Modeling.vtt 2.1 KB
  2. Bias-Variance Trade-Off.mp4 4.9 MB
  2. Bias-Variance Trade-Off.vtt 3.6 KB
  2. Bootstrap Demo.mp4 11 MB
  2. Bootstrap Demo.vtt 3.6 KB
  2. Confidence Intervals.mp4 12.6 MB
  2. Confidence Intervals.vtt 11.5 KB
  2. Random Forest Regressor.mp4 14.9 MB
  2. Random Forest Regressor.vtt 7.5 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. AdaBoost Loss Function Exponential Loss.mp4 11.2 MB
  3. AdaBoost Loss Function Exponential Loss.vtt 7.4 KB
  3. All Data is the Same.mp4 5.3 MB
  3. All Data is the Same.vtt 3.9 KB
  3. Bagging.mp4 3.9 MB
  3. Bagging.vtt 2.7 KB
  3. Bias-Variance Decomposition.mp4 5.4 MB
  3. Bias-Variance Decomposition.vtt 3.5 KB
  3. Random Forest Classifier.mp4 12.6 MB
  3. Random Forest Classifier.vtt 5 KB
  3. Windows-Focused Environment Setup 2018.mp4 186.3 MB
  3. Windows-Focused Environment Setup 2018.vtt 17.4 KB
  4. AdaBoost Implementation.mp4 15.8 MB
  4. AdaBoost Implementation.vtt 9.6 KB
  4. Bagging Regression Trees.mp4 15.9 MB
  4. Bagging Regression Trees.vtt 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
  4. Plug-and-Play.mp4 3.5 MB
  4. Plug-and-Play.vtt 2.6 KB
  4. Polynomial Regression Demo.mp4 41.8 MB
  4. Polynomial Regression Demo.vtt 11.4 KB
  4. Random Forest vs Bagging Trees.mp4 7.8 MB
  4. Random Forest vs Bagging Trees.vtt 3.9 KB
  5. Bagging Classification Trees.mp4 20.3 MB
  5. Bagging Classification Trees.vtt 4.8 KB
  5. Comparison to Stacking.mp4 5.5 MB
  5. Comparison to Stacking.vtt 3.8 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
  5. Implementing a Not as Random Forest.mp4 8.7 MB
  5. Implementing a Not as Random Forest.vtt 4.4 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. Connection to Deep Learning Dropout.mp4 4.2 MB
  6. Connection to Deep Learning Dropout.vtt 2.8 KB
  6. Connection to Deep Learning.mp4 6 MB
  6. Connection to Deep Learning.vtt 4.2 KB
  6. Cross-Validation as a Method for Optimizing Model Complexity.mp4 7 MB
  6. Cross-Validation as a Method for Optimizing Model Complexity.vtt 5.1 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
  6. Stacking.mp4 6.1 MB
  6. Stacking.vtt 4.5 KB
  7. How to Succeed in this Course (Long Version).mp4 13 MB
  7. How to Succeed in this Course (Long Version).vtt 12.9 KB
  7. Summary and What's Next.mp4 7.4 MB
  7. Summary and What's Next.vtt 5.5 KB
  8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39 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 B
  ▲ 85 total files

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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