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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
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| 1. AdaBoost and XGBoost classifier.mp4 |
67.66Мб |
| 1. AdaBoost and XGBoost classifier.srt |
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| 1. AdaBoost and XGBoost regressor.mp4 |
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| 1. AdaBoost and XGBoost regressor.srt |
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| 1. Autocomplete on jupyter notebook.mp4 |
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| 1. Autocomplete on jupyter notebook.srt |
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| 1. Bagging.mp4 |
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| 1. Bagging.srt |
12.83Кб |
| 1. Bayes theorem.mp4 |
73.79Мб |
| 1. Bayes theorem.srt |
22.20Кб |
| 1. Bias, Variance and overfitting.mp4 |
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| 1. Bias, Variance and overfitting.srt |
12.28Кб |
| 1. Classification model master template.mp4 |
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| 1. Classification model master template.srt |
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| 1. Data import.mp4 |
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| 1. Data import.srt |
10.58Кб |
| 1. Data types.mp4 |
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| 1. Data types.srt |
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| 1. Decision Tree and Random forest.mp4 |
59.49Мб |
| 1. Decision Tree and Random forest.srt |
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| 1. Ensemble Learning.mp4 |
52.57Мб |
| 1. Ensemble Learning.srt |
9.92Кб |
| 1. Euler's number.mp4 |
52.69Мб |
| 1. Euler's number.srt |
18.11Кб |
| 1. Files introduction.mp4 |
16.81Мб |
| 1. Files introduction.srt |
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| 1. If ElIf & else.mp4 |
45.31Мб |
| 1. If ElIf & else.srt |
13.98Кб |
| 1. Introduction to ML & Supervised learning.mp4 |
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| 1. Introduction to ML & Supervised learning.srt |
14.05Кб |
| 1. K Fold cross validation.mp4 |
20.01Мб |
| 1. K Fold cross validation.srt |
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| 1. KNN background.mp4 |
62.26Мб |
| 1. KNN background.srt |
18.09Кб |
| 1. Linear regression working and Cost function.mp4 |
37.60Мб |
| 1. Linear regression working and Cost function.srt |
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| 1. Master template regression model - Data creation.mp4 |
134.74Мб |
| 1. Master template regression model - Data creation.srt |
22.85Кб |
| 1. Matplotlib simple plot, line graphs.mp4 |
54.56Мб |
| 1. Matplotlib simple plot, line graphs.srt |
13.62Кб |
| 1. Matrices.mp4 |
23.32Мб |
| 1. Matrices.srt |
10.22Кб |
| 1. Measuring Entropy & Gini impurity.mp4 |
81.94Мб |
| 1. Measuring Entropy & Gini impurity.srt |
21.27Кб |
| 1. Model deployment basics.mp4 |
51.39Мб |
| 1. Model deployment basics.srt |
9.19Кб |
| 1. Multiple linear regression in Python.mp4 |
69.61Мб |
| 1. Multiple linear regression in Python.srt |
12.70Кб |
| 1. Naming conventions and introduction.mp4 |
51.97Мб |
| 1. Naming conventions and introduction.srt |
14.80Кб |
| 1. Panda series.mp4 |
42.26Мб |
| 1. Panda series.srt |
13.27Кб |
| 1. Polynomial regression.mp4 |
143.82Мб |
| 1. Polynomial regression.srt |
23.00Кб |
| 1. Python decorators.mp4 |
72.83Мб |
| 1. Python decorators.srt |
17.72Кб |
| 1. Python packages.mp4 |
86.78Мб |
| 1. Python packages.srt |
11.13Кб |
| 1. Python random class.mp4 |
70.59Мб |
| 1. Python random class.srt |
18.64Кб |
| 1. Python setting up.mp4 |
76.70Мб |
| 1. Python setting up.srt |
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| 1. Regular expression introduction.mp4 |
72.46Мб |
| 1. Regular expression introduction.srt |
15.65Кб |
| 1. ROC, AUC and PR curve background.mp4 |
131.44Мб |
| 1. R-square.mp4 |
51.66Мб |
| 1. R-square.srt |
17.49Кб |
| 1. Setting up.mp4 |
44.98Мб |
| 1. Setting up.srt |
11.65Кб |
| 1. SVM (regression) Background.mp4 |
26.94Мб |
| 1. SVM (regression) Background.srt |
7.89Кб |
| 1. SVM getting started with 1D data.mp4 |
57.31Мб |
| 1. SVM getting started with 1D data.srt |
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| 1. Thanks for taking this course.mp4 |
29.77Мб |
| 1. Thanks for taking this course.srt |
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| 1. The accuracy, not so accurate.mp4 |
46.01Мб |
| 1. The accuracy, not so accurate.srt |
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| 1. Try except finally.mp4 |
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| 1. Try except finally.srt |
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| 1. Updated template with GridSearchCV.mp4 |
109.00Мб |
| 1. Updated template with GridSearchCV.srt |
13.76Кб |
| 1. User-defined functions.mp4 |
47.47Мб |
| 1. User-defined functions.srt |
15.79Кб |
| 1. Voting classifier.mp4 |
114.74Мб |
| 1. Voting classifier.srt |
19.05Кб |
| 1. Why Co-relation is important.mp4 |
110.46Мб |
| 1. Why Co-relation is important.srt |
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| 1. Why Logistic regression.mp4 |
51.02Мб |
| 1. Why Logistic regression.srt |
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| 10. Sets.mp4 |
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| 11. Tuples.mp4 |
26.73Мб |
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| 12. Dictionary in python.mp4 |
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| 12. Dictionary in python.srt |
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| 13. None and Bool.mp4 |
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| 14. Comparison operators.mp4 |
28.30Мб |
| 14. Comparison operators.srt |
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| 15. Logical operators.mp4 |
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| 15. Logical operators.srt |
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| 16. Connect on LinkedIn, It's good!.mp4 |
71.04Мб |
| 16. Connect on LinkedIn, It's good!.srt |
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| 2 |
1.33Мб |
| 2. Adjusted R-Square.mp4 |
21.56Мб |
| 2. Adjusted R-Square.srt |
7.39Кб |
| 2. Balanced vs imbalanced data.mp4 |
28.07Мб |
| 2. Balanced vs imbalanced data.srt |
8.28Кб |
| 2. Boosting.mp4 |
63.93Мб |
| 2. Boosting.srt |
18.83Кб |
| 2. Class attributes and Methods.mp4 |
41.19Мб |
| 2. Class attributes and Methods.srt |
11.93Кб |
| 2. Classification model master template with evaluation and different data set.mp4 |
75.15Мб |
| 2. Classification model master template with evaluation and different data set.srt |
11.90Кб |
| 2. Class method decorator.mp4 |
52.76Мб |
| 2. Class method decorator.srt |
11.53Кб |
| 2. Confusion matrix.mp4 |
38.24Мб |
| 2. Confusion matrix.srt |
9.75Кб |
| 2. Co-variance.mp4 |
57.34Мб |
| 2. Co-variance.srt |
17.50Кб |
| 2. DataFrame introduction.mp4 |
98.14Мб |
| 2. DataFrame introduction.srt |
25.46Кб |
| 2. Decision Tree implementation with 1 feature.mp4 |
53.80Мб |
| 2. Decision Tree implementation with 1 feature.srt |
15.65Кб |
| 2. Error types, else and finally.mp4 |
86.25Мб |
| 2. Error types, else and finally.srt |
16.79Кб |
| 2. Gradient decent - Background.mp4 |
60.51Мб |
| 2. Gradient decent - Background.srt |
19.68Кб |
| 2. handling missing data.mp4 |
71.55Мб |
| 2. handling missing data.srt |
14.74Кб |
| 2. Help function.mp4 |
23.59Мб |
| 2. Help function.srt |
7.27Кб |
| 2. Jupyter notebook.mp4 |
95.43Мб |
| 2. Jupyter notebook.srt |
15.08Кб |
| 2. KNN in python.mp4 |
48.73Мб |
| 2. KNN in python.srt |
8.86Кб |
| 2. Likelihood vs probability.mp4 |
52.32Мб |
| 2. Likelihood vs probability.srt |
10.92Кб |
| 2. Linear regression implementation in python - Part 1.mp4 |
92.47Мб |
| 2. Linear regression implementation in python - Part 1.srt |
21.97Кб |
| 2. Logistic regression background.mp4 |
52.01Мб |
| 2. Logistic regression background.srt |
15.14Кб |
| 2. Master template regression model - Models and evaluation.mp4 |
21.98Мб |
| 2. Master template regression model - Models and evaluation.srt |
3.94Кб |
| 2. Matplotlib Bar-graph and multiple plotting.mp4 |
68.58Мб |
| 2. Matplotlib Bar-graph and multiple plotting.srt |
14.01Кб |
| 2. Matrix operations and scalar operations.mp4 |
13.99Мб |
| 2. Matrix operations and scalar operations.srt |
5.84Кб |
| 2. Multiple linear regression behind the scene - Part 1.mp4 |
160.26Мб |
| 2. Multiple linear regression behind the scene - Part 1.srt |
20.98Кб |
| 2. NumPy array functions - Array generate.mp4 |
44.64Мб |
| 2. NumPy array functions - Array generate.srt |
15.77Кб |
| 2. Paths.mp4 |
62.83Мб |
| 2. Paths.srt |
15.98Кб |
| 2. Polynomial regression on multiple feature dataset.mp4 |
119.27Мб |
| 2. Polynomial regression on multiple feature dataset.srt |
27.97Кб |
| 2. Prediction using value.mp4 |
54.35Мб |
| 2. Prediction using value.srt |
9.19Кб |
| 2. Python numbers.mp4 |
28.92Мб |
| 2. Python numbers.srt |
10.08Кб |
| 2. Random Forest.mp4 |
52.61Мб |
| 2. Random Forest.srt |
10.14Кб |
| 2. RandomizedSearchCV.mp4 |
115.41Мб |
| 2. RandomizedSearchCV.srt |
12.11Кб |
| 2. Random under numpy and Arange.mp4 |
77.09Мб |
| 2. Random under numpy and Arange.srt |
17.60Кб |
| 2. Regular expression, grouping and pipe.mp4 |
48.18Мб |
| 2. Regular expression, grouping and pipe.srt |
14.11Кб |
| 2. ROC, AUC - Evaluating best model.mp4 |
61.12Мб |
| 2. ROC, AUC - Evaluating best model.srt |
9.71Кб |
| 2. Scatter plot on Iris dataset.mp4 |
153.44Мб |
| 2. Scatter plot on Iris dataset.srt |
23.26Кб |
| 2. SVM, mapping higher dimension.mp4 |
47.80Мб |
| 2. SVM, mapping higher dimension.srt |
15.63Кб |
| 2. SVR under Python.mp4 |
21.73Мб |
| 2. SVR under Python.srt |
4.01Кб |
| 2. Unsupervised learning.mp4 |
52.50Мб |
| 2. Unsupervised learning.srt |
9.25Кб |
| 2. Updated template with GridSearchCV.mp4 |
143.32Мб |
| 2. Updated template with GridSearchCV.srt |
24.17Кб |
| 2. User defined packages.mp4 |
144.43Мб |
| 2. User defined packages.srt |
20.06Кб |
| 2. While loop.mp4 |
32.48Мб |
| 2. While loop.srt |
11.13Кб |
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368.92Кб |
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| 3 |
187.87Кб |
| 3. Accuracy, precision, recall, Specificity, F1 Score.mp4 |
66.10Мб |
| 3. Accuracy, precision, recall, Specificity, F1 Score.srt |
14.76Кб |
| 3. Co-relation.mp4 |
57.39Мб |
| 3. Co-relation.srt |
13.78Кб |
| 3. DataFrame Selections.mp4 |
75.65Мб |
| 3. DataFrame Selections.srt |
18.70Кб |
| 3. Feature selection and Encoding categorical data.mp4 |
48.21Мб |
| 3. Feature selection and Encoding categorical data.srt |
10.23Кб |
| 3. For loop.mp4 |
35.00Мб |
| 3. For loop.srt |
10.71Кб |
| 3. Gradient decent in 2D and 3D space.mp4 |
85.14Мб |
| 3. Gradient decent in 2D and 3D space.srt |
13.11Кб |
| 3. Inheritance.mp4 |
41.99Мб |
| 3. Inheritance.srt |
12.58Кб |
| 3. K Fold cross validation without GridSearchCV.mp4 |
91.91Мб |
| 3. K Fold cross validation without GridSearchCV.srt |
19.21Кб |
| 3. Linear regression implementation in python - Part 2.mp4 |
35.27Мб |
| 3. Linear regression implementation in python - Part 2.srt |
7.82Кб |
| 3. Logistic regression under python.mp4 |
41.68Мб |
| 3. Logistic regression under python.srt |
6.81Кб |
| 3. Matplotlib Subplot and histogram.mp4 |
82.54Мб |
| 3. Matplotlib Subplot and histogram.srt |
25.37Кб |
| 3. Matrix multiplication.mp4 |
23.39Мб |
| 3. Matrix multiplication.srt |
8.50Кб |
| 3. Multinomial naive bayes.mp4 |
65.01Мб |
| 3. Multinomial naive bayes.srt |
16.90Кб |
| 3. Multiple linear regression behind the scene - Part 2.mp4 |
75.10Мб |
| 3. Multiple linear regression behind the scene - Part 2.srt |
17.37Кб |
| 3. Pair plot and limitations.mp4 |
67.83Мб |
| 3. Pair plot and limitations.srt |
13.40Кб |
| 3. Pycharm python IDE.mp4 |
60.50Мб |
| 3. Pycharm python IDE.srt |
8.76Кб |
| 3. Python collections.mp4 |
64.02Мб |
| 3. Python collections.srt |
17.05Кб |
| 3. Python generators.mp4 |
76.10Мб |
| 3. Python generators.srt |
17.50Кб |
| 3. Random array based methods.mp4 |
57.40Мб |
| 3. Random array based methods.srt |
14.15Кб |
| 3. Read mode, write mode and methods.mp4 |
97.06Мб |
| 3. Read mode, write mode and methods.srt |
19.09Кб |
| 3. Repetition and range.mp4 |
71.55Мб |
| 3. Repetition and range.srt |
12.98Кб |
| 3. ROC, AUC - Calculating the optimal threshold (Youdens method).mp4 |
124.39Мб |
| 3. ROC, AUC - Calculating the optimal threshold (Youdens method).srt |
21.02Кб |
| 3. Scopes.mp4 |
60.95Мб |
| 3. Scopes.srt |
16.24Кб |
| 3. SVM, in 2D space.mp4 |
44.62Мб |
| 3. SVM, in 2D space.srt |
11.64Кб |
| 3. Type of data.mp4 |
23.76Мб |
| 3. Type of data.srt |
9.09Кб |
| 3. User defined packages continues.mp4 |
57.59Мб |
| 3. User defined packages continues.srt |
6.56Кб |
| 3. Variables and assignment.mp4 |
31.81Мб |
| 3. Variables and assignment.srt |
9.12Кб |
| 3. Visualization and few more things.mp4 |
59.82Мб |
| 3. Visualization and few more things.srt |
9.32Кб |
| 3. Visualization of decision tree model.mp4 |
89.29Мб |
| 3. Visualization of decision tree model.srt |
15.92Кб |
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1.22Мб |
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701.17Кб |
| 4. args and kwargs.mp4 |
50.95Мб |
| 4. args and kwargs.srt |
12.51Кб |
| 4. Confusion matrix 3D.mp4 |
74.97Мб |
| 4. Confusion matrix 3D.srt |
15.32Кб |
| 4. Curse of dimensionality.mp4 |
33.81Мб |
| 4. Curse of dimensionality.srt |
9.65Кб |
| 4. Decision Tree implementation - multiple features.mp4 |
53.75Мб |
| 4. Decision Tree implementation - multiple features.srt |
10.23Кб |
| 4. Greedy, non-greedy matches and findall.mp4 |
61.45Мб |
| 4. Greedy, non-greedy matches and findall.srt |
15.03Кб |
| 4. GroupBy.mp4 |
37.28Мб |
| 4. GroupBy.srt |
10.22Кб |
| 4. K Fold cross validation without GridSearchCV continues.mp4 |
68.43Мб |
| 4. K Fold cross validation without GridSearchCV continues.srt |
10.21Кб |
| 4. LabelEncoding classes.mp4 |
47.16Мб |
| 4. LabelEncoding classes.srt |
8.17Кб |
| 4. Logistic regression on multi-class classification.mp4 |
42.81Мб |
| 4. Logistic regression on multi-class classification.srt |
12.37Кб |
| 4. Matplotlib Scatter plots and Pie charts.mp4 |
48.53Мб |
| 4. Matplotlib Scatter plots and Pie charts.srt |
12.05Кб |
| 4. Mean Mode median.mp4 |
15.96Мб |
| 4. Mean Mode median.srt |
6.66Кб |
| 4. Multiple, multi level inheritance and MRO.mp4 |
79.77Мб |
| 4. Multiple, multi level inheritance and MRO.srt |
19.95Кб |
| 4. Python counter from collections.mp4 |
54.21Мб |
| 4. Python counter from collections.srt |
14.01Кб |
| 4. ROC, AUC - Calculating the optimal threshold (best Accuracy method).mp4 |
69.34Мб |
| 4. ROC, AUC - Calculating the optimal threshold (best Accuracy method).srt |
12.55Кб |
| 4. Slicing and broadcast.mp4 |
44.14Мб |
| 4. Slicing and broadcast.srt |
16.24Кб |
| 4. String basics.mp4 |
35.29Мб |
| 4. String basics.srt |
10.02Кб |
| 4. SVM implementation using python.mp4 |
64.16Мб |
| 4. SVM implementation using python.srt |
10.42Кб |
| 4. Test and train data split and Feature scaling.mp4 |
97.95Мб |
| 4. Test and train data split and Feature scaling.srt |
20.78Кб |
| 4. The log scale.mp4 |
83.64Мб |
| 4. The log scale.srt |
26.21Кб |
| 4. Tips dataset.mp4 |
26.08Мб |
| 4. Tips dataset.srt |
4.19Кб |
| 4. Tuple unpacking.mp4 |
31.28Мб |
| 4. Tuple unpacking.srt |
11.97Кб |
| 4. Update Anaconda website updated.mp4 |
56.04Мб |
| 4. Update Anaconda website updated.srt |
9.32Кб |
| 4. Vector Multiplication.mp4 |
82.95Мб |
| 4. Vector Multiplication.srt |
15.54Кб |
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1.30Мб |
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216.14Кб |
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1.17Мб |
| 49 |
1.54Мб |
| 5 |
334.99Кб |
| 5. BeginsWith endsWith and dot character.mp4 |
86.88Мб |
| 5. BeginsWith endsWith and dot character.srt |
21.90Кб |
| 5. Break, continue and pass.mp4 |
37.34Мб |
| 5. Break, continue and pass.srt |
15.03Кб |
| 5. CAP curve background.mp4 |
53.90Мб |
| 5. CAP curve background.srt |
14.31Кб |
| 5. Concatenation.mp4 |
72.27Мб |
| 5. Concatenation.srt |
14.51Кб |
| 5. Gaussian naive bayes.mp4 |
77.43Мб |
| 5. Gaussian naive bayes.srt |
20.80Кб |
| 5. Identity matrix, matrix inverse properties, transpose of matrix.mp4 |
28.77Мб |
| 5. Identity matrix, matrix inverse properties, transpose of matrix.srt |
9.02Кб |
| 5. KNN on multi class classification.mp4 |
44.32Мб |
| 5. KNN on multi class classification.srt |
8.50Кб |
| 5. Logistic regression on multi-class classification under python.mp4 |
29.53Мб |
| 5. Logistic regression on multi-class classification under python.srt |
3.72Кб |
| 5. Maps, Filters and Lambdas.mp4 |
67.55Мб |
| 5. Maps, Filters and Lambdas.srt |
20.81Кб |
| 5. Math Matrix multiplication.mp4 |
24.07Мб |
| 5. Math Matrix multiplication.srt |
8.82Кб |
| 5. Matplotlib 3D scatter and simple plot.mp4 |
54.46Мб |
| 5. Matplotlib 3D scatter and simple plot.srt |
10.78Кб |
| 5. Matrices selection and conditional selection.mp4 |
54.39Мб |
| 5. Matrices selection and conditional selection.srt |
19.23Кб |
| 5. Meet your Author.mp4 |
42.10Мб |
| 5. Meet your Author.srt |
2.47Кб |
| 5. Polymorphism.mp4 |
41.14Мб |
| 5. Polymorphism.srt |
13.03Кб |
| 5. Pre-processing re-visited.mp4 |
110.43Мб |
| 5. Pre-processing re-visited.srt |
19.53Кб |
| 5. Seaborn plots.mp4 |
95.29Мб |
| 5. Seaborn plots.srt |
26.15Кб |
| 5. Standard deviation.mp4 |
32.77Мб |
| 5. Standard deviation.srt |
14.76Кб |
| 5. String Start Stop and Step.mp4 |
61.02Мб |
| 5. String Start Stop and Step.srt |
16.38Кб |
| 5. Under and over sampling.mp4 |
87.64Мб |
| 5. Under and over sampling.srt |
17.03Кб |
| 50 |
1.73Мб |
| 51 |
456.44Кб |
| 52 |
465.68Кб |
| 53 |
813.60Кб |
| 54 |
982.67Кб |
| 55 |
983.39Кб |
| 56 |
1.41Мб |
| 57 |
397.42Кб |
| 58 |
674.29Кб |
| 59 |
1.42Мб |
| 6 |
1.26Мб |
| 6. Assignment and tips.mp4 |
32.58Мб |
| 6. Assignment and tips.srt |
4.49Кб |
| 6. BeginsWith endsWith and dot character continues.mp4 |
28.65Мб |
| 6. BeginsWith endsWith and dot character continues.srt |
8.46Кб |
| 6. CAP curve implementation.mp4 |
66.97Мб |
| 6. CAP curve implementation.srt |
12.99Кб |
| 6. Facetgrid plots.mp4 |
44.71Мб |
| 6. Facetgrid plots.srt |
11.38Кб |
| 6. Gaussian naive Bayes under Python & Visualization of models.mp4 |
88.47Мб |
| 6. Gaussian naive Bayes under Python & Visualization of models.srt |
14.79Кб |
| 6. Lambda once again.mp4 |
49.68Мб |
| 6. Lambda once again.srt |
12.91Кб |
| 6. Linkedin and Instagram links.html |
511б |
| 6. Matpotlib Wireframe surface plotting.mp4 |
57.02Мб |
| 6. Matpotlib Wireframe surface plotting.srt |
12.92Кб |
| 6. Most common data distributions, PDF and PMF.mp4 |
51.44Мб |
| 6. Most common data distributions, PDF and PMF.srt |
11.03Кб |
| 6. Numpy operations.mp4 |
40.69Мб |
| 6. Numpy operations.srt |
9.08Кб |
| 6. Operations.mp4 |
32.99Мб |
| 6. Operations.srt |
10.42Кб |
| 6. Pre-processing re-visited continues.mp4 |
71.21Мб |
| 6. Pre-processing re-visited continues.srt |
12.51Кб |
| 6. Range, enumerate and zip.mp4 |
75.00Мб |
| 6. Range, enumerate and zip.srt |
25.78Кб |
| 6. Special class methods.mp4 |
65.81Мб |
| 6. Special class methods.srt |
17.52Кб |
| 6. String slicing.mp4 |
20.04Мб |
| 6. String slicing.srt |
5.90Кб |
| 60 |
1.57Мб |
| 61 |
174.25Кб |
| 62 |
348.48Кб |
| 63 |
456.03Кб |
| 64 |
1.03Мб |
| 65 |
1.03Мб |
| 66 |
1.90Мб |
| 67 |
193.25Кб |
| 68 |
1017.43Кб |
| 69 |
1.84Мб |
| 7 |
571.55Кб |
| 7. About Project files.mp4 |
57.65Мб |
| 7. About Project files.srt |
3.22Кб |
| 7. Assignment solution and OneHotEncoding - Part 01.mp4 |
113.21Мб |
| 7. Assignment solution and OneHotEncoding - Part 01.srt |
20.19Кб |
| 7. CAP curve with multiple models and multi-class.mp4 |
135.67Мб |
| 7. CAP curve with multiple models and multi-class.srt |
20.08Кб |
| 7. Feature selection.mp4 |
106.13Мб |
| 7. Feature selection.srt |
16.99Кб |
| 7. In.mp4 |
28.47Мб |
| 7. In.srt |
11.01Кб |
| 7. Percentiles, moment and Quantiles.mp4 |
88.76Мб |
| 7. Percentiles, moment and Quantiles.srt |
15.85Кб |
| 7. Sets.mp4 |
37.51Мб |
| 7. Sets.srt |
12.24Кб |
| 7. String formatting.mp4 |
38.45Мб |
| 7. String formatting.srt |
9.63Кб |
| 7. Univariate Analysis using PDF.mp4 |
57.29Мб |
| 7. Univariate Analysis using PDF.srt |
13.98Кб |
| 70 |
1.98Мб |
| 71 |
75.44Кб |
| 72 |
1.17Мб |
| 73 |
1.74Мб |
| 74 |
393.00Кб |
| 75 |
562.04Кб |
| 76 |
905.17Кб |
| 77 |
1006.18Кб |
| 78 |
1.05Мб |
| 79 |
1.49Мб |
| 8 |
1.78Мб |
| 8. Assignment solution and OneHotEncoding - Part 02.mp4 |
126.22Мб |
| 8. Assignment solution and OneHotEncoding - Part 02.srt |
19.21Кб |
| 8. Boxplot and Violin Plot.mp4 |
53.07Мб |
| 8. Boxplot and Violin Plot.srt |
17.65Кб |
| 8. Input and import.mp4 |
28.00Мб |
| 8. Input and import.srt |
9.73Кб |
| 8. Lists in Python.mp4 |
33.36Мб |
| 8. Lists in Python.srt |
9.99Кб |
| 8. Literal matching, Sub and verbose.mp4 |
39.87Мб |
| 8. Literal matching, Sub and verbose.srt |
12.01Кб |
| 8. Short discussion.mp4 |
26.28Мб |
| 8. Short discussion.srt |
3.74Кб |
| 80 |
1.50Мб |
| 81 |
182.11Кб |
| 82 |
524.45Кб |
| 83 |
104.79Кб |
| 84 |
356.59Кб |
| 85 |
421.81Кб |
| 86 |
617.08Кб |
| 87 |
623.17Кб |
| 88 |
675.30Кб |
| 89 |
710.39Кб |
| 9 |
1.61Мб |
| 9. Discussion forum.mp4 |
61.62Мб |
| 9. Discussion forum.srt |
3.77Кб |
| 9. HeatMap.mp4 |
42.78Мб |
| 9. HeatMap.srt |
12.43Кб |
| 9. List shorting, reversing, removing, clear, list of list.mp4 |
44.09Мб |
| 9. List shorting, reversing, removing, clear, list of list.srt |
12.90Кб |
| 90 |
729.77Кб |
| 91 |
1000.13Кб |
| 92 |
1.96Мб |
| 93 |
1.44Мб |
| 94 |
1.51Мб |
| 95 |
1.54Мб |
| 96 |
1.61Мб |
| 97 |
1.65Мб |
| 98 |
1.79Мб |
| 99 |
1.99Мб |
| TutsNode.com.txt |
63б |