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种子名称： [Tutorialsplanet.NET] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost
文件类型： 视频
文件数目： 43个文件
文件大小： 884.95 MB
收录时间： 2020-8-28 02:03
已经下载： 3次
资源热度： 95
最近下载： 2024-6-12 17:27

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[Tutorialsplanet.NET] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost.torrent

1. Get Started/1. Outline and Motivation.mp47.19MB

1. Get Started/2. Where to get the Code and Data.mp43.36MB

1. Get Started/3. All Data is the Same.mp45.24MB

1. Get Started/4. Plug-and-Play.mp43.5MB

10. Appendix FAQ/1. What is the Appendix.mp45.46MB

10. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp437.84MB

2. Bias-Variance Trade-Off/1. Bias-Variance Key Terms.mp410.24MB

2. Bias-Variance Trade-Off/2. Bias-Variance Trade-Off.mp44.89MB

2. Bias-Variance Trade-Off/3. Bias-Variance Decomposition.mp414.3MB

2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.mp441.76MB

2. Bias-Variance Trade-Off/5. K-Nearest Neighbor and Decision Tree Demo.mp413.86MB

2. Bias-Variance Trade-Off/6. Cross-Validation as a Method for Optimizing Model Complexity.mp46.98MB

2. Bias-Variance Trade-Off/7. Suggestion Box.mp416.12MB

3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.mp447.73MB

3. Bootstrap Estimates and Bagging/2. Bootstrap Demo.mp410.96MB

3. Bootstrap Estimates and Bagging/3. Bagging.mp43.93MB

3. Bootstrap Estimates and Bagging/4. Bagging Regression Trees.mp415.88MB

3. Bootstrap Estimates and Bagging/5. Bagging Classification Trees.mp420.32MB

3. Bootstrap Estimates and Bagging/6. Stacking.mp46.08MB

4. Random Forest/1. Random Forest Algorithm.mp414.43MB

4. Random Forest/2. Random Forest Regressor.mp414.9MB

4. Random Forest/3. Random Forest Classifier.mp412.58MB

4. Random Forest/4. Random Forest vs Bagging Trees.mp47.82MB

4. Random Forest/5. Implementing a Not as Random Forest.mp48.69MB

4. Random Forest/6. Connection to Deep Learning Dropout.mp44.22MB

5. AdaBoost/1. AdaBoost Algorithm.mp410.88MB

5. AdaBoost/2. Additive Modeling.mp42.81MB

5. AdaBoost/3. AdaBoost Loss Function Exponential Loss.mp411.19MB

5. AdaBoost/4. AdaBoost Implementation.mp415.79MB

5. AdaBoost/5. Comparison to Stacking.mp45.44MB

5. AdaBoost/6. Connection to Deep Learning.mp46.03MB

5. AdaBoost/7. Summary and What's Next.mp47.37MB

6. Background Review/1. Confidence Intervals.mp412.6MB

7. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4186.3MB

7. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB

8. Extra Help With Python Coding for Beginners/1. How to Code by Yourself (part 1).mp424.54MB

8. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 2).mp414.8MB

8. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp478.26MB

8. Extra Help With Python Coding for Beginners/4. Python 2 vs Python 3.mp47.83MB

9/1. How to Succeed in this Course (Long Version).mp413MB

9/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.96MB

9/3. What order should I take your courses in (part 1).mp429.33MB

9/4. What order should I take your courses in (part 2).mp437.63MB