Udemy The Supervised Machine Learning Bootcamp

Files Included :

1 - Introduction.mp4 (69.89 MB)
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2 - Installing Anaconda.mp4 (29.53 MB)
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3 - Jupyter Dashboard Part 1.mp4 (10.25 MB)
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4 - Jupyter Dashboard Part 2.mp4 (20.99 MB)
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5 - Installing the relevant packages.mp4 (22.78 MB)
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10 - The HamorSpam Example.mp4 (66.89 MB)
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12 - Notebooks-and-Dataset.zip (168.87 KB)
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12 - The YouTube Dataset Creating the Data Frame.mp4 (33.75 MB)
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13 - CountVectorizer.mp4 (36.99 MB)
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14 - The YouTube Dataset Preprocessing.mp4 (43.97 MB)
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15 - youtube-dataset.zip (158.79 KB)
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16 - The YouTube Dataset Classification.mp4 (23.67 MB)
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17 - youtube-dataset.zip (158.79 KB)
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18 - The YouTube Dataset Confusion Matrix.mp4 (17.79 MB)
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19 - The YouTube Dataset Accuracy Precision Recall and the F1 score.mp4 (37.74 MB)
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20 - The YouTube Dataset Changing the Priors.mp4 (40.34 MB)
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6 - Motivation.mp4 (43.38 MB)
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7 - Bayes Thought Experiment.mp4 (33.66 MB)
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9 - Bayes Theorem.mp4 (65.92 MB)
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22 - Motivation.mp4 (24.43 MB)
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23 - Math Prerequisites Distance Metrics.mp4 (27.79 MB)
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24 - KNeighborsClassifier-Notebooks.zip (9.54 KB)
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24 - Random Dataset Generating the Dataset.mp4 (16.85 MB)
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25 - Random Dataset Visualizing the Dataset.mp4 (28.19 MB)
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26 - Random Dataset Classification.mp4 (50.6 MB)
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27 - Random Dataset How to Break a Tie.mp4 (26.76 MB)
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28 - Random Dataset Decision Regions.mp4 (46 MB)
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29 - Random Dataset Choosing the Best Kvalue.mp4 (32.64 MB)
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30 - Random Dataset Grid Search.mp4 (27.88 MB)
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31 - Random Dataset Model Performance.mp4 (21.21 MB)
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32 - KNeighborsClassifier-Exercise.zip (7.91 KB)
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33 - KNeighborsRegressor-Notebooks.zip (4.73 KB)
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33 - Theory with a Practical Example.mp4 (43.75 MB)
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34 - KNN vs Linear Regression A Linear Problem.mp4 (46.73 MB)
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34 - LinearProblem-Notebooks.zip (5.4 KB)
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35 - KNN vs Linear Regression A Nonlinear Problem.mp4 (33.11 MB)
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35 - NonLinearProblem-Notebooks.zip (5.77 KB)
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36 - KNeighborsRegressor-Exercise.zip (290.68 KB)
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37 - Pros and Cons.mp4 (55.22 MB)
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38 - What is a Tree in Computer Science.mp4 (34.84 MB)
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39 - The Concept of Decision Trees.mp4 (31.62 MB)
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40 - Decision Trees in Machine Learning.mp4 (47.34 MB)
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41 - Decision Trees Pros and Cons.mp4 (69.13 MB)
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42 - Practical Example The Iris Dataset.mp4 (21.83 MB)
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43 - Practical Example Creating a Decision Tree.mp4 (32.83 MB)
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44 - Practical Example Plotting the Tree.mp4 (42.97 MB)
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45 - Decision Tree Metrics Intuition Gini Inpurity.mp4 (53.2 MB)
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46 - Decision Tree Metrics Information Gain.mp4 (26.36 MB)
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47 - Tree Pruning Dealing with Overfitting.mp4 (39.41 MB)
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48 - Random Forest as Ensemble Learning.mp4 (31.99 MB)
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49 - Bootstrapping.mp4 (29.92 MB)
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50 - From Bootstrapping to Random Forests.mp4 (25.93 MB)
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51 - Glass-dataset.zip (3.66 KB)
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51 - Random Forest in Code Glass Dataset.mp4 (52.81 MB)
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52 - Census Data and Income Preprocessing.mp4 (59.6 MB)
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52 - Census-Income-Dataset.zip (612.27 KB)
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53 - Training the Decision Tree.mp4 (27.35 MB)
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54 - Training the Random Forest.mp4 (27.17 MB)
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55 - Introduction to Support Vector Machines.mp4 (62.4 MB)
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56 - Linearly separable classes hard margin problem.mp4 (59.15 MB)
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57 - Nonlinearly separable classes soft margin problem.mp4 (49.84 MB)
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58 - Kernels Intuition.mp4 (77.05 MB)
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59 - Intro to the practical case.mp4 (31.54 MB)
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60 - Preprocessing the data.mp4 (15.06 MB)
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61 - Splitting the data into train and test and rescaling.mp4 (16.4 MB)
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62 - Implementing a linear SVM.mp4 (12.66 MB)
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63 - Analyzing the results– Confusion Matrix Precision and Recall.mp4 (28.22 MB)
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64 - Crossvalidation.mp4 (76.47 MB)
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65 - Choosing the kernels and C values for crossvalidation.mp4 (18.81 MB)
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66 - Hyperparameter tuning using GridSearchCV.mp4 (35.14 MB)
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68 - Regression Analysis Overview.mp4 (29.41 MB)
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69 - Overfitting and Multicollinearity.mp4 (28.15 MB)
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70 - Introduction to Regularization.mp4 (25.96 MB)
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71 - Ridge Regression Basics.mp4 (43.16 MB)
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72 - Ridge Regression Mechanics.mp4 (46.67 MB)
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73 - Regularization in More Complicated Scenarios.mp4 (21 MB)
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74 - Lasso Regression Basics.mp4 (21.63 MB)
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75 - Lasso Regression vs Ridge Regression.mp4 (33.86 MB)
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76 - The Hitters Dataset Preprocessing and Preparation.mp4 (46 MB)
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77 - Exploratory Data Analysis.mp4 (36.96 MB)
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78 - Performing Linear Regression.mp4 (52.93 MB)
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79 - Crossvalidation for Choosing a Tuning Parameter.mp4 (30.49 MB)
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80 - Performing Ridge Regression with Crossvalidation.mp4 (30.97 MB)
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81 - Performing Lasso Regression with Crossvalidation.mp4 (30.96 MB)
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82 - Comparing the Results.mp4 (30.97 MB)
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83 - Replacing the Missing Values in the DataFrame.mp4 (21.22 MB)
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