Download Free Download : Udemy Data Science in Python Classification Modeling BOOKWARE-SOFTiMAGE
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:3.36 GB
Files Included :
1 Course Introduction.mp4 (29.33 MB)
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2 About This Series.mp4 (3.65 MB)
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3 Course Structure & Outline.mp4 (11.83 MB)
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4 Course Structure & Outline.mp4 (11.83 MB)
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7 Introducing the Course Project.mp4 (4.47 MB)
MP4
8 Setting Expectations.mp4 (10.1 MB)
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9 Jupyter Installation & Launch.mp4 (23.83 MB)
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1 Decision Trees.mp4 (18.02 MB)
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10 DEMO Hyperparameter Tuning.mp4 (22.86 MB)
MP4
11 ASSIGNMENT Tuned Decision Tree.mp4 (3.55 MB)
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12 SOLUTION Tuned Decision Tree.mp4 (26.58 MB)
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13 Pros & Cons of Decision Trees.mp4 (16.66 MB)
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14 Key Takeaways.mp4 (6.45 MB)
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2 Entropy.mp4 (24 MB)
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3 Decision Tree Predictions.mp4 (20.83 MB)
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4 Decision Trees in Python.mp4 (15.84 MB)
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5 DEMO Decision Trees.mp4 (32.33 MB)
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6 Feature Importance.mp4 (28.29 MB)
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7 ASSIGNMENT Decision Trees.mp4 (5.66 MB)
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8 SOLUTION Decision Trees.mp4 (35.14 MB)
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9 Hyperparameter Tuning for Decision Trees.mp4 (26.21 MB)
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1 Ensemble Models.mp4 (20.89 MB)
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10 Pros & Cons of Random Forests.mp4 (10.82 MB)
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11 ASSIGNMENT Random Forests.mp4 (5.17 MB)
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12 SOLUTION Random Forests.mp4 (43.63 MB)
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13 Gradient Boosting.mp4 (9.61 MB)
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14 Gradient Boosting in Python.mp4 (12.4 MB)
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15 Hyperparameter Tuning for Gradient Boosting.mp4 (28.53 MB)
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16 DEMO Hyperparameter Tuning for Gradient Boosting.mp4 (22.92 MB)
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17 Pros & Cons of Gradient Boosting.mp4 (10.74 MB)
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18 ASSIGNMENT Gradient Boosting.mp4 (4.94 MB)
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19 SOLUTION Gradient Boosting.mp4 (30.41 MB)
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2 Simple Ensemble Models.mp4 (12.34 MB)
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20 PRO TIP SHAP Values.mp4 (32.12 MB)
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21 DEMO SHAP Values.mp4 (28.72 MB)
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22 Key Takeaways.mp4 (6.35 MB)
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3 DEMO Simple Ensemble Models.mp4 (26.33 MB)
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4 ASSIGNMENT Simple Ensemble Models.mp4 (8.2 MB)
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5 SOLUTION Simple Ensemble Models.mp4 (27.41 MB)
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6 Random Forests.mp4 (6.3 MB)
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7 Fitting Random Forests in Python.mp4 (21.7 MB)
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8 Hyperparameter Tuning for Random Forests.mp4 (28.25 MB)
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9 PRO TIP Random Search.mp4 (36.68 MB)
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1 Recap Classification Models & Workflow.mp4 (13.96 MB)
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2 Pros & Cons of Classification Models.mp4 (20.18 MB)
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3 DEMO Production Pipeline & Deployment.mp4 (75.26 MB)
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4 Looking Ahead Unsupervised Learning.mp4 (5.53 MB)
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1 Project Brief.mp4 (16.25 MB)
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2 Solution Walkthrough.mp4 (55.88 MB)
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1 What is Data Science.mp4 (12.27 MB)
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2 The Data Science Skillset.mp4 (7.28 MB)
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3 What is Machine Learning.mp4 (13.95 MB)
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4 Common Machine Learning Algorithms.mp4 (10.34 MB)
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5 Data Science Workflow.mp4 (5.54 MB)
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6 Data Prep & EDA Steps.mp4 (20 MB)
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7 Modeling Steps.mp4 (17.16 MB)
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8 Classification Modeling.mp4 (3.57 MB)
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9 Key Takeaways.mp4 (7.58 MB)
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1 Classification 101.mp4 (29.24 MB)
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2 Goals of Classification.mp4 (10.45 MB)
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3 Types of Classification.mp4 (10.53 MB)
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4 Classification Modeling Workflow.mp4 (13.92 MB)
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5 Key Takeaways.mp4 (7.87 MB)
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1 EDA For Classification.mp4 (18.15 MB)
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10 PRO TIP Correlation Matrix.mp4 (12.57 MB)
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11 DEMO Correlation Matrix.mp4 (31.34 MB)
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12 Feature-Target Relationships.mp4 (37.09 MB)
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13 Feature-Feature Relationships.mp4 (13.91 MB)
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14 PRO TIP Pair Plots.mp4 (43.73 MB)
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15 ASSIGNMENT Exploring Relationships.mp4 (11.66 MB)
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16 SOLUTION Exploring Relationships.mp4 (51.22 MB)
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17 Feature Engineering Overview.mp4 (24.06 MB)
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18 Numeric Feature Engineering.mp4 (22.87 MB)
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19 Dummy Variables.mp4 (24.54 MB)
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2 Defining a Target.mp4 (21.9 MB)
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20 Binning Categories.mp4 (19.29 MB)
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21 DEMO Feature Engineering.mp4 (44.63 MB)
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22 Data Splitting.mp4 (31.68 MB)
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23 Preparing Data for Modeling.mp4 (9.47 MB)
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24 ASSIGNMENT Preparing the Data for Modeling.mp4 (7.55 MB)
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25 SOLUTION Prepare the Data for Modeling.mp4 (57.3 MB)
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26 Key Takeaways.mp4 (7.28 MB)
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3 DEMO Defining a Target.mp4 (36.24 MB)
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4 Exploring the Target.mp4 (19.65 MB)
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5 Exploring the Features.mp4 (10.39 MB)
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6 DEMO Exploring the Features.mp4 (28.35 MB)
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7 ASSIGNMENT Exploring the Target & Features.mp4 (14.16 MB)
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8 SOLUTION Exploring the Target & Features.mp4 (39.29 MB)
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9 Correlation.mp4 (21.7 MB)
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1 K-Nearest Neighbors.mp4 (30.63 MB)
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10 Overfitting & Validation.mp4 (37.35 MB)
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11 DEMO Hyperparameter Tuning.mp4 (29.67 MB)
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12 Hard vs Soft Classification.mp4 (23.36 MB)
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13 DEMO Probability vs Event Rate.mp4 (59.04 MB)
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14 ASSIGNMENT Tuning a KNN Model.mp4 (7.33 MB)
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15 SOLUTION Tuning a KNN Model.mp4 (24.76 MB)
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16 Pros & Cons of KNN.mp4 (25.96 MB)
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17 Key Takeaways.mp4 (6.08 MB)
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2 The KNN Workflow.mp4 (27.29 MB)
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3 KNN in Python.mp4 (11.87 MB)
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4 Model Accuracy.mp4 (20.78 MB)
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5 Confusion Matrix.mp4 (20.09 MB)
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6 DEMO Confusion Matrix.mp4 (23.28 MB)
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7 ASSIGNMENT Fitting a Simple KNN Model.mp4 (10.84 MB)
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8 SOLUTION Fitting a Simple KNN Model.mp4 (28.13 MB)
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9 Hyperparameter Tuning.mp4 (16.36 MB)
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1 Logistic Regression.mp4 (15.26 MB)
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10 SOLUTION Logistic Regression.mp4 (24.45 MB)
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11 Feature Engineering & Selection.mp4 (21.69 MB)
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12 Regularization.mp4 (24.41 MB)
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13 Tuning a Regularized Model.mp4 (21.43 MB)
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14 DEMO Regularized Logistic Regression.mp4 (31.28 MB)
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15 ASSIGNMENT Regularized Logistic Regression.mp4 (6.87 MB)
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16 SOLUTION Regularized Logistic Regression.mp4 (43.56 MB)
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17 Multi-class Logistic Regression.mp4 (34.54 MB)
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18 ASSIGNMENT Multi-class Logistic Regression.mp4 (8.19 MB)
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19 SOLUTION Multi-class Logistic Regression.mp4 (19.88 MB)
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2 Logistic vs Linear Regression.mp4 (11.99 MB)
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20 Pros & Cons of Logistic Regression.mp4 (16.28 MB)
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21 Key Takeaways.mp4 (7.95 MB)
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3 The Logistic Function.mp4 (14.23 MB)
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4 Likelihood.mp4 (23.36 MB)
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5 Multiple Logistic Regression.mp4 (14.14 MB)
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6 The Logistic Regression Workflow.mp4 (4.41 MB)
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7 Logistic Regression in Python.mp4 (27.9 MB)
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8 Interpreting Coefficients.mp4 (21.08 MB)
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9 ASSIGNMENT Logistic Regression.mp4 (9.5 MB)
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1 Classification Metrics.mp4 (13.55 MB)
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10 DEMO Plotting Precision-Recall & F1 Curves.mp4 (23.48 MB)
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11 The ROC Curve & AUC.mp4 (19.02 MB)
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12 DEMO The ROC Curve & AUC.mp4 (19.83 MB)
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13 Classification Metrics Recap.mp4 (14.82 MB)
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14 ASSIGNMENT Threshold Shifting.mp4 (7.01 MB)
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15 SOLUTION Threshold Shifting.mp4 (36.73 MB)
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16 Multi-class Metrics.mp4 (29.77 MB)
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17 Multi-class Metrics in Python.mp4 (8.48 MB)
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18 ASSIGNMENT Multi-class Metrics.mp4 (6.24 MB)
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19 SOLUTION Multi-class Metrics.mp4 (16.62 MB)
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2 Accuracy, Precision & Recall.mp4 (29.58 MB)
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20 Key Takeaways.mp4 (9.89 MB)
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3 DEMO Accuracy, Precision & Recall.mp4 (33.87 MB)
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4 PRO TIP F1 Score.mp4 (18.68 MB)
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5 ASSIGNMENT Model Metrics.mp4 (5.29 MB)
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6 SOLUTION Model Metrics.mp4 (24.32 MB)
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7 Soft Classification.mp4 (31.1 MB)
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8 DEMO Leveraging Soft Classification.mp4 (19.75 MB)
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9 PRO TIP Precision-Recall & F1 Curves.mp4 (20.92 MB)
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1 Imbalanced Data.mp4 (23.47 MB)
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10 Undersampling.mp4 (9.84 MB)
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11 Undersampling in Python.mp4 (33.41 MB)
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12 ASSIGNMENT Sampling Methods.mp4 (16.99 MB)
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13 SOLUTION Sampling Methods.mp4 (45.33 MB)
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14 Changing Class Weights.mp4 (16.56 MB)
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15 DEMO Changing Class Weights.mp4 (21.35 MB)
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16 ASSIGNMENT Changing Class Weights.mp4 (4.27 MB)
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17 SOLUTION Changing Class Weights.mp4 (21.91 MB)
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18 Imbalanced Data Recap.mp4 (8.28 MB)
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19 Key Takeaways.mp4 (5.55 MB)
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2 Managing Imbalanced Data.mp4 (21.26 MB)
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3 Threshold Shifting.mp4 (11.26 MB)
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4 Sampling Strategies.mp4 (10.64 MB)
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5 Oversampling.mp4 (7.25 MB)
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6 Oversampling in Python.mp4 (15.4 MB)
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7 DEMO Oversampling.mp4 (28.13 MB)
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8 SMOTE.mp4 (5.67 MB)
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9 SMOTE in Python.mp4 (14.87 MB)
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1 Project Brief.mp4 (24.21 MB)
MP4
2 Solution Walkthrough.mp4 (75.86 MB)
MP4
MP4
2 About This Series.mp4 (3.65 MB)
MP4
3 Course Structure & Outline.mp4 (11.83 MB)
MP4
4 Course Structure & Outline.mp4 (11.83 MB)
MP4
7 Introducing the Course Project.mp4 (4.47 MB)
MP4
8 Setting Expectations.mp4 (10.1 MB)
MP4
9 Jupyter Installation & Launch.mp4 (23.83 MB)
MP4
1 Decision Trees.mp4 (18.02 MB)
MP4
10 DEMO Hyperparameter Tuning.mp4 (22.86 MB)
MP4
11 ASSIGNMENT Tuned Decision Tree.mp4 (3.55 MB)
MP4
12 SOLUTION Tuned Decision Tree.mp4 (26.58 MB)
MP4
13 Pros & Cons of Decision Trees.mp4 (16.66 MB)
MP4
14 Key Takeaways.mp4 (6.45 MB)
MP4
2 Entropy.mp4 (24 MB)
MP4
3 Decision Tree Predictions.mp4 (20.83 MB)
MP4
4 Decision Trees in Python.mp4 (15.84 MB)
MP4
5 DEMO Decision Trees.mp4 (32.33 MB)
MP4
6 Feature Importance.mp4 (28.29 MB)
MP4
7 ASSIGNMENT Decision Trees.mp4 (5.66 MB)
MP4
8 SOLUTION Decision Trees.mp4 (35.14 MB)
MP4
9 Hyperparameter Tuning for Decision Trees.mp4 (26.21 MB)
MP4
1 Ensemble Models.mp4 (20.89 MB)
MP4
10 Pros & Cons of Random Forests.mp4 (10.82 MB)
MP4
11 ASSIGNMENT Random Forests.mp4 (5.17 MB)
MP4
12 SOLUTION Random Forests.mp4 (43.63 MB)
MP4
13 Gradient Boosting.mp4 (9.61 MB)
MP4
14 Gradient Boosting in Python.mp4 (12.4 MB)
MP4
15 Hyperparameter Tuning for Gradient Boosting.mp4 (28.53 MB)
MP4
16 DEMO Hyperparameter Tuning for Gradient Boosting.mp4 (22.92 MB)
MP4
17 Pros & Cons of Gradient Boosting.mp4 (10.74 MB)
MP4
18 ASSIGNMENT Gradient Boosting.mp4 (4.94 MB)
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19 SOLUTION Gradient Boosting.mp4 (30.41 MB)
MP4
2 Simple Ensemble Models.mp4 (12.34 MB)
MP4
20 PRO TIP SHAP Values.mp4 (32.12 MB)
MP4
21 DEMO SHAP Values.mp4 (28.72 MB)
MP4
22 Key Takeaways.mp4 (6.35 MB)
MP4
3 DEMO Simple Ensemble Models.mp4 (26.33 MB)
MP4
4 ASSIGNMENT Simple Ensemble Models.mp4 (8.2 MB)
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5 SOLUTION Simple Ensemble Models.mp4 (27.41 MB)
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6 Random Forests.mp4 (6.3 MB)
MP4
7 Fitting Random Forests in Python.mp4 (21.7 MB)
MP4
8 Hyperparameter Tuning for Random Forests.mp4 (28.25 MB)
MP4
9 PRO TIP Random Search.mp4 (36.68 MB)
MP4
1 Recap Classification Models & Workflow.mp4 (13.96 MB)
MP4
2 Pros & Cons of Classification Models.mp4 (20.18 MB)
MP4
3 DEMO Production Pipeline & Deployment.mp4 (75.26 MB)
MP4
4 Looking Ahead Unsupervised Learning.mp4 (5.53 MB)
MP4
1 Project Brief.mp4 (16.25 MB)
MP4
2 Solution Walkthrough.mp4 (55.88 MB)
MP4
1 What is Data Science.mp4 (12.27 MB)
MP4
2 The Data Science Skillset.mp4 (7.28 MB)
MP4
3 What is Machine Learning.mp4 (13.95 MB)
MP4
4 Common Machine Learning Algorithms.mp4 (10.34 MB)
MP4
5 Data Science Workflow.mp4 (5.54 MB)
MP4
6 Data Prep & EDA Steps.mp4 (20 MB)
MP4
7 Modeling Steps.mp4 (17.16 MB)
MP4
8 Classification Modeling.mp4 (3.57 MB)
MP4
9 Key Takeaways.mp4 (7.58 MB)
MP4
1 Classification 101.mp4 (29.24 MB)
MP4
2 Goals of Classification.mp4 (10.45 MB)
MP4
3 Types of Classification.mp4 (10.53 MB)
MP4
4 Classification Modeling Workflow.mp4 (13.92 MB)
MP4
5 Key Takeaways.mp4 (7.87 MB)
MP4
1 EDA For Classification.mp4 (18.15 MB)
MP4
10 PRO TIP Correlation Matrix.mp4 (12.57 MB)
MP4
11 DEMO Correlation Matrix.mp4 (31.34 MB)
MP4
12 Feature-Target Relationships.mp4 (37.09 MB)
MP4
13 Feature-Feature Relationships.mp4 (13.91 MB)
MP4
14 PRO TIP Pair Plots.mp4 (43.73 MB)
MP4
15 ASSIGNMENT Exploring Relationships.mp4 (11.66 MB)
MP4
16 SOLUTION Exploring Relationships.mp4 (51.22 MB)
MP4
17 Feature Engineering Overview.mp4 (24.06 MB)
MP4
18 Numeric Feature Engineering.mp4 (22.87 MB)
MP4
19 Dummy Variables.mp4 (24.54 MB)
MP4
2 Defining a Target.mp4 (21.9 MB)
MP4
20 Binning Categories.mp4 (19.29 MB)
MP4
21 DEMO Feature Engineering.mp4 (44.63 MB)
MP4
22 Data Splitting.mp4 (31.68 MB)
MP4
23 Preparing Data for Modeling.mp4 (9.47 MB)
MP4
24 ASSIGNMENT Preparing the Data for Modeling.mp4 (7.55 MB)
MP4
25 SOLUTION Prepare the Data for Modeling.mp4 (57.3 MB)
MP4
26 Key Takeaways.mp4 (7.28 MB)
MP4
3 DEMO Defining a Target.mp4 (36.24 MB)
MP4
4 Exploring the Target.mp4 (19.65 MB)
MP4
5 Exploring the Features.mp4 (10.39 MB)
MP4
6 DEMO Exploring the Features.mp4 (28.35 MB)
MP4
7 ASSIGNMENT Exploring the Target & Features.mp4 (14.16 MB)
MP4
8 SOLUTION Exploring the Target & Features.mp4 (39.29 MB)
MP4
9 Correlation.mp4 (21.7 MB)
MP4
1 K-Nearest Neighbors.mp4 (30.63 MB)
MP4
10 Overfitting & Validation.mp4 (37.35 MB)
MP4
11 DEMO Hyperparameter Tuning.mp4 (29.67 MB)
MP4
12 Hard vs Soft Classification.mp4 (23.36 MB)
MP4
13 DEMO Probability vs Event Rate.mp4 (59.04 MB)
MP4
14 ASSIGNMENT Tuning a KNN Model.mp4 (7.33 MB)
MP4
15 SOLUTION Tuning a KNN Model.mp4 (24.76 MB)
MP4
16 Pros & Cons of KNN.mp4 (25.96 MB)
MP4
17 Key Takeaways.mp4 (6.08 MB)
MP4
2 The KNN Workflow.mp4 (27.29 MB)
MP4
3 KNN in Python.mp4 (11.87 MB)
MP4
4 Model Accuracy.mp4 (20.78 MB)
MP4
5 Confusion Matrix.mp4 (20.09 MB)
MP4
6 DEMO Confusion Matrix.mp4 (23.28 MB)
MP4
7 ASSIGNMENT Fitting a Simple KNN Model.mp4 (10.84 MB)
MP4
8 SOLUTION Fitting a Simple KNN Model.mp4 (28.13 MB)
MP4
9 Hyperparameter Tuning.mp4 (16.36 MB)
MP4
1 Logistic Regression.mp4 (15.26 MB)
MP4
10 SOLUTION Logistic Regression.mp4 (24.45 MB)
MP4
11 Feature Engineering & Selection.mp4 (21.69 MB)
MP4
12 Regularization.mp4 (24.41 MB)
MP4
13 Tuning a Regularized Model.mp4 (21.43 MB)
MP4
14 DEMO Regularized Logistic Regression.mp4 (31.28 MB)
MP4
15 ASSIGNMENT Regularized Logistic Regression.mp4 (6.87 MB)
MP4
16 SOLUTION Regularized Logistic Regression.mp4 (43.56 MB)
MP4
17 Multi-class Logistic Regression.mp4 (34.54 MB)
MP4
18 ASSIGNMENT Multi-class Logistic Regression.mp4 (8.19 MB)
MP4
19 SOLUTION Multi-class Logistic Regression.mp4 (19.88 MB)
MP4
2 Logistic vs Linear Regression.mp4 (11.99 MB)
MP4
20 Pros & Cons of Logistic Regression.mp4 (16.28 MB)
MP4
21 Key Takeaways.mp4 (7.95 MB)
MP4
3 The Logistic Function.mp4 (14.23 MB)
MP4
4 Likelihood.mp4 (23.36 MB)
MP4
5 Multiple Logistic Regression.mp4 (14.14 MB)
MP4
6 The Logistic Regression Workflow.mp4 (4.41 MB)
MP4
7 Logistic Regression in Python.mp4 (27.9 MB)
MP4
8 Interpreting Coefficients.mp4 (21.08 MB)
MP4
9 ASSIGNMENT Logistic Regression.mp4 (9.5 MB)
MP4
1 Classification Metrics.mp4 (13.55 MB)
MP4
10 DEMO Plotting Precision-Recall & F1 Curves.mp4 (23.48 MB)
MP4
11 The ROC Curve & AUC.mp4 (19.02 MB)
MP4
12 DEMO The ROC Curve & AUC.mp4 (19.83 MB)
MP4
13 Classification Metrics Recap.mp4 (14.82 MB)
MP4
14 ASSIGNMENT Threshold Shifting.mp4 (7.01 MB)
MP4
15 SOLUTION Threshold Shifting.mp4 (36.73 MB)
MP4
16 Multi-class Metrics.mp4 (29.77 MB)
MP4
17 Multi-class Metrics in Python.mp4 (8.48 MB)
MP4
18 ASSIGNMENT Multi-class Metrics.mp4 (6.24 MB)
MP4
19 SOLUTION Multi-class Metrics.mp4 (16.62 MB)
MP4
2 Accuracy, Precision & Recall.mp4 (29.58 MB)
MP4
20 Key Takeaways.mp4 (9.89 MB)
MP4
3 DEMO Accuracy, Precision & Recall.mp4 (33.87 MB)
MP4
4 PRO TIP F1 Score.mp4 (18.68 MB)
MP4
5 ASSIGNMENT Model Metrics.mp4 (5.29 MB)
MP4
6 SOLUTION Model Metrics.mp4 (24.32 MB)
MP4
7 Soft Classification.mp4 (31.1 MB)
MP4
8 DEMO Leveraging Soft Classification.mp4 (19.75 MB)
MP4
9 PRO TIP Precision-Recall & F1 Curves.mp4 (20.92 MB)
MP4
1 Imbalanced Data.mp4 (23.47 MB)
MP4
10 Undersampling.mp4 (9.84 MB)
MP4
11 Undersampling in Python.mp4 (33.41 MB)
MP4
12 ASSIGNMENT Sampling Methods.mp4 (16.99 MB)
MP4
13 SOLUTION Sampling Methods.mp4 (45.33 MB)
MP4
14 Changing Class Weights.mp4 (16.56 MB)
MP4
15 DEMO Changing Class Weights.mp4 (21.35 MB)
MP4
16 ASSIGNMENT Changing Class Weights.mp4 (4.27 MB)
MP4
17 SOLUTION Changing Class Weights.mp4 (21.91 MB)
MP4
18 Imbalanced Data Recap.mp4 (8.28 MB)
MP4
19 Key Takeaways.mp4 (5.55 MB)
MP4
2 Managing Imbalanced Data.mp4 (21.26 MB)
MP4
3 Threshold Shifting.mp4 (11.26 MB)
MP4
4 Sampling Strategies.mp4 (10.64 MB)
MP4
5 Oversampling.mp4 (7.25 MB)
MP4
6 Oversampling in Python.mp4 (15.4 MB)
MP4
7 DEMO Oversampling.mp4 (28.13 MB)
MP4
8 SMOTE.mp4 (5.67 MB)
MP4
9 SMOTE in Python.mp4 (14.87 MB)
MP4
1 Project Brief.mp4 (24.21 MB)
MP4
2 Solution Walkthrough.mp4 (75.86 MB)
MP4
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