|
Обратите внимание, что наш сайт не размещает какие-либо файлы из списка. Вы не можете скачать
эти файлы или скачать torrent-файл.
|
| 0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url |
377б |
| 1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url |
328б |
| 1. BONUS Discounts on my other courses!.html |
1.02Кб |
| 1. Categorical encoding Introduction.mp4 |
34.03Мб |
| 1. Categorical encoding Introduction.srt |
7.93Кб |
| 1. Categorical encoding Introduction.vtt |
7.11Кб |
| 1. Classification pipeline.mp4 |
135.99Мб |
| 1. Classification pipeline.srt |
15.57Кб |
| 1. Classification pipeline.vtt |
13.87Кб |
| 1. Discretisation Introduction.mp4 |
15.45Мб |
| 1. Discretisation Introduction.srt |
3.41Кб |
| 1. Discretisation Introduction.vtt |
3.04Кб |
| 1. Engineering datetime variables.mp4 |
23.19Мб |
| 1. Engineering datetime variables.srt |
5.48Кб |
| 1. Engineering datetime variables.vtt |
4.87Кб |
| 1. Engineering mixed variables.mp4 |
15.27Мб |
| 1. Engineering mixed variables.srt |
3.98Кб |
| 1. Engineering mixed variables.vtt |
3.55Кб |
| 1. Feature scaling Introduction.mp4 |
20.60Мб |
| 1. Feature scaling Introduction.srt |
4.55Кб |
| 1. Feature scaling Introduction.vtt |
4.07Кб |
| 1. Introduction.mp4 |
32.86Мб |
| 1. Introduction.srt |
6.81Кб |
| 1. Introduction.vtt |
6.06Кб |
| 1. Introduction to missing data imputation.mp4 |
29.37Мб |
| 1. Introduction to missing data imputation.srt |
5.24Кб |
| 1. Introduction to missing data imputation.vtt |
4.66Кб |
| 1. Multivariate Imputation - COMING IN 2020.html |
105б |
| 1. Outlier Engineering Intro.mp4 |
41.97Мб |
| 1. Outlier Engineering Intro.srt |
7.70Кб |
| 1. Outlier Engineering Intro.vtt |
6.87Кб |
| 1. Variable characteristics.mp4 |
20.84Мб |
| 1. Variable characteristics.srt |
3.58Кб |
| 1. Variable characteristics.vtt |
3.19Кб |
| 1. Variables Intro.mp4 |
15.30Мб |
| 1. Variables Intro.srt |
3.53Кб |
| 1. Variables Intro.vtt |
3.14Кб |
| 1. Variable Transformation Introduction.mp4 |
18.66Мб |
| 1. Variable Transformation Introduction.srt |
5.48Кб |
| 1. Variable Transformation Introduction.vtt |
4.93Кб |
| 10. Bonus Additional reading resources.html |
4.68Кб |
| 10. Discretisation with classification trees.mp4 |
26.58Мб |
| 10. Discretisation with classification trees.srt |
5.46Кб |
| 10. Discretisation with classification trees.vtt |
4.89Кб |
| 10. Mean or median imputation with Scikit-learn.mp4 |
88.12Мб |
| 10. Mean or median imputation with Scikit-learn.srt |
12.86Кб |
| 10. Mean or median imputation with Scikit-learn.vtt |
11.35Кб |
| 10. Scaling to median and quantiles.mp4 |
13.01Мб |
| 10. Scaling to median and quantiles.srt |
3.15Кб |
| 10. Scaling to median and quantiles.vtt |
2.82Кб |
| 10. Target guided ordinal encoding.mp4 |
12.87Мб |
| 10. Target guided ordinal encoding.srt |
3.43Кб |
| 10. Target guided ordinal encoding.vtt |
3.05Кб |
| 11. Arbitrary value imputation with Scikit-learn.mp4 |
52.16Мб |
| 11. Arbitrary value imputation with Scikit-learn.srt |
6.55Кб |
| 11. Arbitrary value imputation with Scikit-learn.vtt |
5.80Кб |
| 11. Discretisation with decision trees using Scikit-learn.mp4 |
80.16Мб |
| 11. Discretisation with decision trees using Scikit-learn.srt |
13.08Кб |
| 11. Discretisation with decision trees using Scikit-learn.vtt |
11.62Кб |
| 11. FAQ How can I learn more about machine learning.html |
824б |
| 11. Robust Scaling Demo.mp4 |
16.55Мб |
| 11. Robust Scaling Demo.srt |
2.43Кб |
| 11. Robust Scaling Demo.vtt |
2.17Кб |
| 11. Target guided ordinal encoding Demo.mp4 |
68.75Мб |
| 11. Target guided ordinal encoding Demo.srt |
9.39Кб |
| 11. Target guided ordinal encoding Demo.vtt |
8.36Кб |
| 12. Discretisation with decision trees using Feature-engine.mp4 |
28.38Мб |
| 12. Discretisation with decision trees using Feature-engine.srt |
3.90Кб |
| 12. Discretisation with decision trees using Feature-engine.vtt |
3.48Кб |
| 12. Frequent category imputation with Scikit-learn.mp4 |
34.18Мб |
| 12. Frequent category imputation with Scikit-learn.srt |
4.15Кб |
| 12. Frequent category imputation with Scikit-learn.vtt |
3.69Кб |
| 12. Mean encoding.mp4 |
12.84Мб |
| 12. Mean encoding.srt |
2.92Кб |
| 12. Mean encoding.vtt |
2.61Кб |
| 12. Scaling to vector unit length.mp4 |
31.94Мб |
| 12. Scaling to vector unit length.srt |
6.64Кб |
| 12. Scaling to vector unit length.vtt |
5.88Кб |
| 13. Domain knowledge discretisation.mp4 |
25.67Мб |
| 13. Domain knowledge discretisation.srt |
4.08Кб |
| 13. Domain knowledge discretisation.vtt |
3.61Кб |
| 13. Mean encoding Demo.mp4 |
42.05Мб |
| 13. Mean encoding Demo.srt |
6.36Кб |
| 13. Mean encoding Demo.vtt |
5.67Кб |
| 13. Missing category imputation with Scikit-learn.mp4 |
24.61Мб |
| 13. Missing category imputation with Scikit-learn.srt |
3.01Кб |
| 13. Missing category imputation with Scikit-learn.vtt |
2.70Кб |
| 13. Scaling to vector unit length Demo.mp4 |
46.31Мб |
| 13. Scaling to vector unit length Demo.srt |
6.01Кб |
| 13. Scaling to vector unit length Demo.vtt |
5.35Кб |
| 14.1 15.5_Bonus_Additional_reading_resources.zip.zip |
1.03Кб |
| 14. Adding a missing indicator with Scikit-learn.mp4 |
35.67Мб |
| 14. Adding a missing indicator with Scikit-learn.srt |
4.69Кб |
| 14. Adding a missing indicator with Scikit-learn.vtt |
4.15Кб |
| 14. Additional reading resources.html |
1.34Кб |
| 14. Bonus Additional reading resources.html |
1.41Кб |
| 14. Probability ratio encoding.mp4 |
45.65Мб |
| 14. Probability ratio encoding.srt |
7.15Кб |
| 14. Probability ratio encoding.vtt |
6.30Кб |
| 15. Automatic determination of imputation method with Sklearn.mp4 |
80.35Мб |
| 15. Automatic determination of imputation method with Sklearn.srt |
9.03Кб |
| 15. Automatic determination of imputation method with Sklearn.vtt |
7.98Кб |
| 15. Weight of evidence (WoE).mp4 |
20.56Мб |
| 15. Weight of evidence (WoE).srt |
5.09Кб |
| 15. Weight of evidence (WoE).vtt |
4.53Кб |
| 16. Introduction to Feature-engine.mp4 |
40.48Мб |
| 16. Introduction to Feature-engine.srt |
6.43Кб |
| 16. Introduction to Feature-engine.vtt |
5.71Кб |
| 16. Weight of Evidence Demo.mp4 |
45.11Мб |
| 16. Weight of Evidence Demo.srt |
7.97Кб |
| 16. Weight of Evidence Demo.vtt |
7.11Кб |
| 17. Comparison of categorical variable encoding.mp4 |
78.44Мб |
| 17. Comparison of categorical variable encoding.srt |
12.37Кб |
| 17. Comparison of categorical variable encoding.vtt |
10.93Кб |
| 17. Mean or median imputation with Feature-engine.mp4 |
38.64Мб |
| 17. Mean or median imputation with Feature-engine.srt |
5.09Кб |
| 17. Mean or median imputation with Feature-engine.vtt |
4.52Кб |
| 18. Arbitrary value imputation with Feature-engine.mp4 |
26.75Мб |
| 18. Arbitrary value imputation with Feature-engine.srt |
3.26Кб |
| 18. Arbitrary value imputation with Feature-engine.vtt |
2.92Кб |
| 18. Rare label encoding.mp4 |
23.31Мб |
| 18. Rare label encoding.srt |
5.16Кб |
| 18. Rare label encoding.vtt |
4.59Кб |
| 19. End of distribution imputation with Feature-engine.mp4 |
38.87Мб |
| 19. End of distribution imputation with Feature-engine.srt |
5.26Кб |
| 19. End of distribution imputation with Feature-engine.vtt |
4.69Кб |
| 19. Rare label encoding Demo.mp4 |
69.43Мб |
| 19. Rare label encoding Demo.srt |
12.01Кб |
| 19. Rare label encoding Demo.vtt |
10.66Кб |
| 2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url |
286б |
| 2. Complete Case Analysis.mp4 |
46.67Мб |
| 2. Complete Case Analysis.srt |
8.53Кб |
| 2. Complete Case Analysis.vtt |
7.55Кб |
| 2. Course curriculum overview.mp4 |
33.37Мб |
| 2. Course curriculum overview.srt |
7.24Кб |
| 2. Course curriculum overview.vtt |
6.46Кб |
| 2. Engineering dates Demo.mp4 |
54.01Мб |
| 2. Engineering dates Demo.srt |
9.10Кб |
| 2. Engineering dates Demo.vtt |
8.05Кб |
| 2. Engineering mixed variables Demo.mp4 |
45.48Мб |
| 2. Engineering mixed variables Demo.srt |
7.24Кб |
| 2. Engineering mixed variables Demo.vtt |
6.45Кб |
| 2. Equal-width discretisation.mp4 |
21.54Мб |
| 2. Equal-width discretisation.srt |
4.38Кб |
| 2. Equal-width discretisation.vtt |
3.91Кб |
| 2. Missing data.mp4 |
40.11Мб |
| 2. Missing data.srt |
8.97Кб |
| 2. Missing data.vtt |
7.92Кб |
| 2. Numerical variables.mp4 |
26.88Мб |
| 2. Numerical variables.srt |
6.69Кб |
| 2. Numerical variables.vtt |
5.97Кб |
| 2. One hot encoding.mp4 |
31.75Мб |
| 2. One hot encoding.srt |
6.97Кб |
| 2. One hot encoding.vtt |
6.20Кб |
| 2. Outlier trimming.mp4 |
51.09Мб |
| 2. Outlier trimming.srt |
8.33Кб |
| 2. Outlier trimming.vtt |
7.39Кб |
| 2. Regression pipeline.mp4 |
157.57Мб |
| 2. Regression pipeline.srt |
16.77Кб |
| 2. Regression pipeline.vtt |
14.83Кб |
| 2. Standardisation.mp4 |
26.51Мб |
| 2. Standardisation.srt |
6.57Кб |
| 2. Standardisation.vtt |
5.86Кб |
| 2. Variable Transformation with Numpy and SciPy.mp4 |
49.41Мб |
| 2. Variable Transformation with Numpy and SciPy.srt |
8.49Кб |
| 2. Variable Transformation with Numpy and SciPy.vtt |
7.56Кб |
| 20. Binary encoding and feature hashing.mp4 |
30.90Мб |
| 20. Binary encoding and feature hashing.srt |
7.55Кб |
| 20. Binary encoding and feature hashing.vtt |
6.69Кб |
| 20. Frequent category imputation with Feature-engine.mp4 |
16.15Мб |
| 20. Frequent category imputation with Feature-engine.srt |
2.07Кб |
| 20. Frequent category imputation with Feature-engine.vtt |
1.84Кб |
| 21. Bonus Additional reading resources.html |
2.42Кб |
| 21. Missing category imputation with Feature-engine.mp4 |
20.42Мб |
| 21. Missing category imputation with Feature-engine.srt |
2.52Кб |
| 21. Missing category imputation with Feature-engine.vtt |
2.25Кб |
| 22. Random sample imputation with Feature-engine.mp4 |
16.09Мб |
| 22. Random sample imputation with Feature-engine.srt |
2.30Кб |
| 22. Random sample imputation with Feature-engine.vtt |
2.03Кб |
| 23. Adding a missing indicator with Feature-engine.mp4 |
25.90Мб |
| 23. Adding a missing indicator with Feature-engine.srt |
3.91Кб |
| 23. Adding a missing indicator with Feature-engine.vtt |
3.47Кб |
| 24.1 NA_methods_Comparison.pdf.pdf |
273.81Кб |
| 24. Overview of missing value imputation methods.html |
140б |
| 25. Conclusion when to use each missing data imputation method.html |
2.66Кб |
| 3. (NulledPremium.com) Download E-Learning, E-Books, Audio-Books, Comics, Articles and more... etc.url |
163б |
| 3. Beat the performance by engineering features.html |
155б |
| 3. Cardinality - categorical variables.mp4 |
31.02Мб |
| 3. Cardinality - categorical variables.srt |
6.34Кб |
| 3. Cardinality - categorical variables.vtt |
5.64Кб |
| 3. Categorical variables.mp4 |
18.40Мб |
| 3. Categorical variables.srt |
4.56Кб |
| 3. Categorical variables.vtt |
4.07Кб |
| 3. Course requirements.mp4 |
10.64Мб |
| 3. Course requirements.srt |
4.10Кб |
| 3. Course requirements.vtt |
3.66Кб |
| 3. Engineering time variables and different timezones.mp4 |
33.48Мб |
| 3. Engineering time variables and different timezones.srt |
5.36Кб |
| 3. Engineering time variables and different timezones.vtt |
4.73Кб |
| 3. Equal-width discretisation Demo.mp4 |
79.10Мб |
| 3. Equal-width discretisation Demo.srt |
12.52Кб |
| 3. Equal-width discretisation Demo.vtt |
11.05Кб |
| 3. Mean or median imputation.mp4 |
52.15Мб |
| 3. Mean or median imputation.srt |
10.29Кб |
| 3. Mean or median imputation.vtt |
9.11Кб |
| 3. One-hot-encoding Demo.mp4 |
91.40Мб |
| 3. One-hot-encoding Demo.srt |
17.55Кб |
| 3. One-hot-encoding Demo.vtt |
15.48Кб |
| 3. Outlier capping with IQR.mp4 |
43.57Мб |
| 3. Outlier capping with IQR.srt |
6.75Кб |
| 3. Outlier capping with IQR.vtt |
6.03Кб |
| 3. Standardisation Demo.mp4 |
41.62Мб |
| 3. Standardisation Demo.srt |
5.51Кб |
| 3. Standardisation Demo.vtt |
4.93Кб |
| 3. variable Transformation with Scikit-learn.mp4 |
47.10Мб |
| 3. variable Transformation with Scikit-learn.srt |
7.58Кб |
| 3. variable Transformation with Scikit-learn.vtt |
6.80Кб |
| 4. (FTUApps.com) Download Cracked Developers Applications For Free.url |
239б |
| 4. Arbitrary value imputation.mp4 |
40.09Мб |
| 4. Arbitrary value imputation.srt |
8.42Кб |
| 4. Arbitrary value imputation.vtt |
7.48Кб |
| 4. Date and time variables.mp4 |
9.80Мб |
| 4. Date and time variables.srt |
2.40Кб |
| 4. Date and time variables.vtt |
2.14Кб |
| 4. Equal-frequency discretisation.mp4 |
22.49Мб |
| 4. Equal-frequency discretisation.srt |
4.68Кб |
| 4. Equal-frequency discretisation.vtt |
4.16Кб |
| 4. How to approach this course.html |
1.76Кб |
| 4. Mean normalisation.mp4 |
19.81Мб |
| 4. Mean normalisation.srt |
4.92Кб |
| 4. Mean normalisation.vtt |
4.40Кб |
| 4. One hot encoding of top categories.mp4 |
18.10Мб |
| 4. One hot encoding of top categories.srt |
3.34Кб |
| 4. One hot encoding of top categories.vtt |
2.98Кб |
| 4. Outlier capping with mean and std.mp4 |
34.58Мб |
| 4. Outlier capping with mean and std.srt |
4.81Кб |
| 4. Outlier capping with mean and std.vtt |
4.31Кб |
| 4. Rare Labels - categorical variables.mp4 |
33.86Мб |
| 4. Rare Labels - categorical variables.srt |
6.09Кб |
| 4. Rare Labels - categorical variables.vtt |
5.40Кб |
| 4. Variable transformation with Feature-engine.mp4 |
23.69Мб |
| 4. Variable transformation with Feature-engine.srt |
3.99Кб |
| 4. Variable transformation with Feature-engine.vtt |
3.59Кб |
| 5.1 sample_s2.csv.csv |
9.94Мб |
| 5. End of distribution imputation.mp4 |
28.11Мб |
| 5. End of distribution imputation.srt |
6.02Кб |
| 5. End of distribution imputation.vtt |
5.36Кб |
| 5. Equal-frequency discretisation Demo.mp4 |
47.29Мб |
| 5. Equal-frequency discretisation Demo.srt |
7.67Кб |
| 5. Equal-frequency discretisation Demo.vtt |
6.85Кб |
| 5. Linear models assumptions.mp4 |
68.89Мб |
| 5. Linear models assumptions.srt |
11.48Кб |
| 5. Linear models assumptions.vtt |
10.25Кб |
| 5. Mean normalisation Demo.mp4 |
45.08Мб |
| 5. Mean normalisation Demo.srt |
6.19Кб |
| 5. Mean normalisation Demo.vtt |
5.51Кб |
| 5. Mixed variables.mp4 |
11.25Мб |
| 5. Mixed variables.srt |
2.94Кб |
| 5. Mixed variables.vtt |
2.60Кб |
| 5. One hot encoding of top categories Demo.mp4 |
57.26Мб |
| 5. One hot encoding of top categories Demo.srt |
9.68Кб |
| 5. One hot encoding of top categories Demo.vtt |
8.58Кб |
| 5. Outlier capping with quantiles.mp4 |
24.44Мб |
| 5. Outlier capping with quantiles.srt |
3.50Кб |
| 5. Outlier capping with quantiles.vtt |
3.17Кб |
| 5. Setting up your computer.html |
3.52Кб |
| 6.1 HandsOnPythonCode.zip.zip |
9.24Мб |
| 6. Arbitrary capping.mp4 |
19.69Мб |
| 6. Arbitrary capping.srt |
3.82Кб |
| 6. Arbitrary capping.vtt |
3.41Кб |
| 6. Bonus More about the Lending Club dataset.html |
826б |
| 6. Download Jupyter notebooks.html |
1.26Кб |
| 6. Frequent category imputation.mp4 |
49.77Мб |
| 6. Frequent category imputation.srt |
8.22Кб |
| 6. Frequent category imputation.vtt |
7.33Кб |
| 6. K-means discretisation.mp4 |
18.87Мб |
| 6. K-means discretisation.srt |
4.73Кб |
| 6. K-means discretisation.vtt |
4.17Кб |
| 6. Ordinal encoding Label encoding.mp4 |
9.42Мб |
| 6. Ordinal encoding Label encoding.srt |
2.08Кб |
| 6. Ordinal encoding Label encoding.vtt |
1.85Кб |
| 6. Scaling to minimum and maximum values.mp4 |
17.08Мб |
| 6. Scaling to minimum and maximum values.srt |
3.81Кб |
| 6. Scaling to minimum and maximum values.vtt |
3.39Кб |
| 6. Variable distribution.mp4 |
32.77Мб |
| 6. Variable distribution.srt |
6.48Кб |
| 6. Variable distribution.vtt |
5.76Кб |
| 7. Additional reading resources.html |
387б |
| 7. Download datasets.html |
1.97Кб |
| 7. K-means discretisation Demo.mp4 |
18.83Мб |
| 7. K-means discretisation Demo.srt |
3.23Кб |
| 7. K-means discretisation Demo.vtt |
2.85Кб |
| 7. MinMaxScaling Demo.mp4 |
25.89Мб |
| 7. MinMaxScaling Demo.srt |
3.47Кб |
| 7. MinMaxScaling Demo.vtt |
3.11Кб |
| 7. Missing category imputation.mp4 |
28.17Мб |
| 7. Missing category imputation.srt |
4.82Кб |
| 7. Missing category imputation.vtt |
4.31Кб |
| 7. Ordinal encoding Demo.mp4 |
57.48Мб |
| 7. Ordinal encoding Demo.srt |
9.33Кб |
| 7. Ordinal encoding Demo.vtt |
8.33Кб |
| 7. Outliers.mp4 |
48.36Мб |
| 7. Outliers.srt |
10.40Кб |
| 7. Outliers.vtt |
9.23Кб |
| 7. Quiz about variable types.html |
151б |
| 8.1 FeatureEngineeringSlides.zip.zip |
29.59Мб |
| 8. Count or frequency encoding.mp4 |
15.73Мб |
| 8. Count or frequency encoding.srt |
3.76Кб |
| 8. Count or frequency encoding.vtt |
3.35Кб |
| 8. Discretisation plus categorical encoding.mp4 |
13.31Мб |
| 8. Discretisation plus categorical encoding.srt |
2.76Кб |
| 8. Discretisation plus categorical encoding.vtt |
2.48Кб |
| 8. Download course presentations.html |
764б |
| 8. Maximum absolute scaling.mp4 |
14.60Мб |
| 8. Maximum absolute scaling.srt |
3.29Кб |
| 8. Maximum absolute scaling.vtt |
2.94Кб |
| 8. Random sample imputation.mp4 |
102.66Мб |
| 8. Random sample imputation.srt |
17.65Кб |
| 8. Random sample imputation.vtt |
15.59Кб |
| 8. Variable magnitude.mp4 |
19.96Мб |
| 8. Variable magnitude.srt |
3.87Кб |
| 8. Variable magnitude.vtt |
3.45Кб |
| 9.1 ML_Comparison.pdf.pdf |
297.65Кб |
| 9. Adding a missing indicator.mp4 |
31.09Мб |
| 9. Adding a missing indicator.srt |
6.55Кб |
| 9. Adding a missing indicator.vtt |
5.81Кб |
| 9. Bonus Machine learning algorithms overview.html |
140б |
| 9. Count encoding Demo.mp4 |
32.53Мб |
| 9. Count encoding Demo.srt |
4.93Кб |
| 9. Count encoding Demo.vtt |
4.42Кб |
| 9. Discretisation plus encoding Demo.mp4 |
36.22Мб |
| 9. Discretisation plus encoding Demo.srt |
6.55Кб |
| 9. Discretisation plus encoding Demo.vtt |
5.80Кб |
| 9. FAQ Data Science, Python programming, datasets, presentations and more....html |
1.64Кб |
| 9. MaxAbsScaling Demo.mp4 |
31.47Мб |
| 9. MaxAbsScaling Demo.srt |
4.56Кб |
| 9. MaxAbsScaling Demo.vtt |
4.05Кб |
| How you can help Team-FTU.txt |
237б |