2.53 GB | 14min 38s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 Introduction.mp4 (28.07 MB)
2 Installing Jupyter.mp4 (36.77 MB)
3 How to download Python files.mp4 (33.32 MB)
1 Import Data.mp4 (105.02 MB)
10 10 displaying the distribution of the data using a box plot.mp4 (95.54 MB)
11 11 displaying the distribution of the data by the different categories.mp4 (133.86 MB)
12 12 visualize the relationship between two variables with jointplot.mp4 (135.15 MB)
13 13 calculating the correlation matrix of the DataFrame.mp4 (84.93 MB)
14 14 creating a mask using NumPy.mp4 (57.18 MB)
15 15 creating a color map using seaborn.mp4 (33.63 MB)
16 16 creating a heatmap using seaborn.mp4 (88.84 MB)
17 17 calculating the number of outliers.mp4 (218.25 MB)
18 18 standardizing features.mp4 (58.84 MB)
19 19 Hypothesis testing.mp4 (34.92 MB)
2 2 visualizing missing data in a dataset.mp4 (34.28 MB)
20 20 Normalization.mp4 (131.91 MB)
21 21 split the data into training and testing sets.mp4 (147.05 MB)
22 22 Start traning SVC and Learn Hyperparameters.mp4 (62.61 MB)
23 23 find the best hyperparameter.mp4 (100.41 MB)
24 24 make predictions on the test data and avaluate the model.mp4 (134.81 MB)
25 25 Train RandomForestClassifier.mp4 (101.82 MB)
26 26 Train XGBClassifier.mp4 (63.7 MB)
27 27 Train KNeighborsClassifier.mp4 (47.88 MB)
28 28 Train LGBMClassifier.mp4 (59.79 MB)
29 29 calculate the (ROC) curve and the (AUC) score.mp4 (104.91 MB)
3 3 calculating statistical information.mp4 (57.89 MB)
4 4 checking for duplicate rows in the DataFrame.mp4 (30.43 MB)
5 5 calculating the number of distinct values in each column.mp4 (56.18 MB)
6 6 checking for missing or null values in the DataFrame.mp4 (34.2 MB)
7 7 Cleaning the data.mp4 (71.18 MB)
8 8 creating a new column called 'Label' in the DataFrame.mp4 (78.66 MB)
9 9 creating a histogram plot.mp4 (117.57 MB)
2 Installing Jupyter.mp4 (36.77 MB)
3 How to download Python files.mp4 (33.32 MB)
1 Import Data.mp4 (105.02 MB)
10 10 displaying the distribution of the data using a box plot.mp4 (95.54 MB)
11 11 displaying the distribution of the data by the different categories.mp4 (133.86 MB)
12 12 visualize the relationship between two variables with jointplot.mp4 (135.15 MB)
13 13 calculating the correlation matrix of the DataFrame.mp4 (84.93 MB)
14 14 creating a mask using NumPy.mp4 (57.18 MB)
15 15 creating a color map using seaborn.mp4 (33.63 MB)
16 16 creating a heatmap using seaborn.mp4 (88.84 MB)
17 17 calculating the number of outliers.mp4 (218.25 MB)
18 18 standardizing features.mp4 (58.84 MB)
19 19 Hypothesis testing.mp4 (34.92 MB)
2 2 visualizing missing data in a dataset.mp4 (34.28 MB)
20 20 Normalization.mp4 (131.91 MB)
21 21 split the data into training and testing sets.mp4 (147.05 MB)
22 22 Start traning SVC and Learn Hyperparameters.mp4 (62.61 MB)
23 23 find the best hyperparameter.mp4 (100.41 MB)
24 24 make predictions on the test data and avaluate the model.mp4 (134.81 MB)
25 25 Train RandomForestClassifier.mp4 (101.82 MB)
26 26 Train XGBClassifier.mp4 (63.7 MB)
27 27 Train KNeighborsClassifier.mp4 (47.88 MB)
28 28 Train LGBMClassifier.mp4 (59.79 MB)
29 29 calculate the (ROC) curve and the (AUC) score.mp4 (104.91 MB)
3 3 calculating statistical information.mp4 (57.89 MB)
4 4 checking for duplicate rows in the DataFrame.mp4 (30.43 MB)
5 5 calculating the number of distinct values in each column.mp4 (56.18 MB)
6 6 checking for missing or null values in the DataFrame.mp4 (34.2 MB)
7 7 Cleaning the data.mp4 (71.18 MB)
8 8 creating a new column called 'Label' in the DataFrame.mp4 (78.66 MB)
9 9 creating a histogram plot.mp4 (117.57 MB)
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