[DesireCourse Com] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost
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| Torrent Hash : | C36599619801D7FB84E1C3D652DA4BB26CA9AFCD |
| Torrent Added : | 1 Year+ in Other - Other |
| Torrent Size : | 826.29 MB |
[DesireCourse Com] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost
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Torrent File Content (85 files)
[DesireCourse.Com] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost
1. Get Started
1. Outline and Motivation.mp4 -
1. Get Started
1. Outline and Motivation.mp4 -
7.2 MB
1. Outline and Motivation.vtt -
6.02 KB
2. Where to get the Code and Data.mp4 -
3.36 MB
2. Where to get the Code and Data.vtt -
2.55 KB
3. All Data is the Same.mp4 -
5.25 MB
3. All Data is the Same.vtt -
3.94 KB
4. Plug-and-Play.mp4 -
3.51 MB
4. Plug-and-Play.vtt -
2.58 KB
2. Bias-Variance Trade-Off
1. Bias-Variance Key Terms.mp4 -
1. Bias-Variance Key Terms.mp4 -
10.23 MB
1. Bias-Variance Key Terms.vtt -
7.84 KB
2. Bias-Variance Trade-Off.mp4 -
4.89 MB
2. Bias-Variance Trade-Off.vtt -
3.57 KB
3. Bias-Variance Decomposition.mp4 -
5.37 MB
3. Bias-Variance Decomposition.vtt -
3.51 KB
4. Polynomial Regression Demo.mp4 -
41.75 MB
4. Polynomial Regression Demo.vtt -
11.45 KB
5. K-Nearest Neighbor and Decision Tree Demo.mp4 -
13.86 MB
5. K-Nearest Neighbor and Decision Tree Demo.vtt -
5.06 KB
6. Cross-Validation as a Method for Optimizing Model Complexity.mp4 -
6.97 MB
6. Cross-Validation as a Method for Optimizing Model Complexity.vtt -
5.1 KB
3. Bootstrap Estimates and Bagging
1. Bootstrap Estimation.mp4 -
1. Bootstrap Estimation.mp4 -
47.72 MB
1. Bootstrap Estimation.vtt -
11.03 KB
2. Bootstrap Demo.mp4 -
10.95 MB
2. Bootstrap Demo.vtt -
3.62 KB
3. Bagging.mp4 -
3.93 MB
3. Bagging.vtt -
2.7 KB
4. Bagging Regression Trees.mp4 -
15.87 MB
4. Bagging Regression Trees.vtt -
4.04 KB
5. Bagging Classification Trees.mp4 -
20.32 MB
5. Bagging Classification Trees.vtt -
4.76 KB
6. Stacking.mp4 -
6.07 MB
6. Stacking.vtt -
4.47 KB
4. Random Forest
1. Random Forest Algorithm.mp4 -
1. Random Forest Algorithm.mp4 -
14.42 MB
1. Random Forest Algorithm.vtt -
10.71 KB
2. Random Forest Regressor.mp4 -
14.89 MB
2. Random Forest Regressor.vtt -
7.47 KB
3. Random Forest Classifier.mp4 -
12.59 MB
3. Random Forest Classifier.vtt -
5 KB
4. Random Forest vs Bagging Trees.mp4 -
7.82 MB
4. Random Forest vs Bagging Trees.vtt -
3.9 KB
5. Implementing a Not as Random Forest.mp4 -
8.69 MB
5. Implementing a Not as Random Forest.vtt -
4.42 KB
6. Connection to Deep Learning Dropout.mp4 -
4.22 MB
6. Connection to Deep Learning Dropout.vtt -
2.85 KB
5. AdaBoost
1. AdaBoost Algorithm.mp4 -
1. AdaBoost Algorithm.mp4 -
10.89 MB
1. AdaBoost Algorithm.vtt -
7.96 KB
2. Additive Modeling.mp4 -
2.8 MB
2. Additive Modeling.vtt -
2.07 KB
3. AdaBoost Loss Function Exponential Loss.mp4 -
11.18 MB
3. AdaBoost Loss Function Exponential Loss.vtt -
7.44 KB
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