Udemy Python Data Science Classification Modeling 11 2024 | AC37A548323E874B4A6E3A50908424A48CE40A52

Udemy Python Data Science Classification Modeling 11 2024

Name	Udemy - Python Data Science Classification Modeling (11.2024)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	2.3 GB
Total Files	338
Last Seen
Hash	AC37A548323E874B4A6E3A50908424A48CE40A52

/01 - Introduction/
001 Course Introduction.mp4	30.8 MB
01 - Introduction/
001 Course Introduction.srt	3.2 KB
002 About This Series.mp4	3.8 MB
002 About This Series.srt	1.2 KB
003 Course Structure & Outline.mp4	12.4 MB
003 Course Structure & Outline.srt	4.1 KB
004 READ ME Important Notes for New Students.html	4.9 KB
005 Data-Science-in-Python-Classification.pdf	36.0 MB
005 Data-Science-in-Python-Classification.zip	103.2 MB
005 DOWNLOAD Course Resources.html	0.5 KB
006 Introducing the Course Project.mp4	4.7 MB
006 Introducing the Course Project.srt	1.5 KB
007 Setting Expectations.mp4	10.6 MB
007 Setting Expectations.srt	2.5 KB
008 Jupyter Installation & Launch.mp4	25.0 MB
008 Jupyter Installation & Launch.srt	7.2 KB
02 - Intro to Data Science/
001 What is Data Science.mp4	5.5 MB
001 What is Data Science.srt	4.8 KB
002 The Data Science Skillset.mp4	3.5 MB
002 The Data Science Skillset.srt	3.0 KB
003 What is Machine Learning.mp4	6.4 MB
003 What is Machine Learning.srt	4.6 KB
004 Common Machine Learning Algorithms.mp4	4.5 MB
004 Common Machine Learning Algorithms.srt	3.4 KB
005 Data Science Workflow.mp4	2.5 MB
005 Data Science Workflow.srt	1.9 KB
006 Data Prep & EDA Steps.mp4	8.8 MB
006 Data Prep & EDA Steps.srt	6.4 KB
007 Modeling Steps.mp4	7.5 MB
007 Modeling Steps.srt	5.1 KB
008 Classification Modeling.mp4	3.7 MB
008 Classification Modeling.srt	1.1 KB
009 Key Takeaways.mp4	3.0 MB
009 Key Takeaways.srt	2.1 KB
03 - Classification 101/
001 Classification 101.mp4	12.9 MB
001 Classification 101.srt	9.6 KB
002 Goals of Classification.mp4	4.5 MB
002 Goals of Classification.srt	3.2 KB
003 Types of Classification.mp4	11.0 MB
003 Types of Classification.srt	4.0 KB
004 Classification Modeling Workflow.mp4	6.8 MB
004 Classification Modeling Workflow.srt	5.0 KB
005 Key Takeaways.mp4	3.2 MB
005 Key Takeaways.srt	2.2 KB
04 - Data Prep & EDA/
001 EDA For Classification.mp4	8.0 MB
001 EDA For Classification.srt	6.1 KB
002 Defining a Target.mp4	10.1 MB
002 Defining a Target.srt	7.8 KB
003 DEMO Defining a Target.mp4	38.0 MB
003 DEMO Defining a Target.srt	9.6 KB
004 Exploring the Target.mp4	12.6 MB
004 Exploring the Target.srt	7.4 KB
005 Exploring the Features.mp4	5.0 MB
005 Exploring the Features.srt	4.0 KB
006 DEMO Exploring the Features.mp4	11.5 MB
006 DEMO Exploring the Features.srt	8.8 KB
007 ASSIGNMENT Exploring the Target & Features.mp4	8.4 MB
007 ASSIGNMENT Exploring the Target & Features.srt	4.2 KB
008 SOLUTION Exploring the Target & Features.mp4	23.6 MB
008 SOLUTION Exploring the Target & Features.srt	14.1 KB
009 Correlation.mp4	10.8 MB
009 Correlation.srt	8.8 KB
010 PRO TIP Correlation Matrix.mp4	5.9 MB
010 PRO TIP Correlation Matrix.srt	4.1 KB
011 DEMO Correlation Matrix.mp4	32.9 MB
011 DEMO Correlation Matrix.srt	8.1 KB
012 Feature-Target Relationships.mp4	22.3 MB
012 Feature-Target Relationships.srt	12.3 KB
013 Feature-Feature Relationships.mp4	6.2 MB
013 Feature-Feature Relationships.srt	4.4 KB
014 PRO TIP Pair Plots.mp4	38.9 MB
014 PRO TIP Pair Plots.srt	7.6 KB
015 ASSIGNMENT Exploring Relationships.mp4	5.4 MB
015 ASSIGNMENT Exploring Relationships.srt	2.9 KB
016 SOLUTION Exploring Relationships.mp4	27.8 MB
016 SOLUTION Exploring Relationships.srt	14.3 KB
017 Feature Engineering Overview.mp4	12.9 MB
017 Feature Engineering Overview.srt	8.7 KB
018 Numeric Feature Engineering.mp4	10.3 MB
018 Numeric Feature Engineering.srt	7.5 KB
019 Dummy Variables.mp4	11.2 MB
019 Dummy Variables.srt	7.9 KB
020 Binning Categories.mp4	8.5 MB
020 Binning Categories.srt	5.8 KB
021 DEMO Feature Engineering.mp4	25.6 MB
021 DEMO Feature Engineering.srt	12.0 KB
022 Data Splitting.mp4	33.2 MB
022 Data Splitting.srt	9.0 KB
023 Preparing Data for Modeling.mp4	4.5 MB
023 Preparing Data for Modeling.srt	3.9 KB
024 ASSIGNMENT Preparing the Data for Modeling.mp4	4.3 MB
024 ASSIGNMENT Preparing the Data for Modeling.srt	3.7 KB
025 SOLUTION Prepare the Data for Modeling.mp4	51.6 MB
025 SOLUTION Prepare the Data for Modeling.srt	12.9 KB
026 Key Takeaways.mp4	3.0 MB
026 Key Takeaways.srt	3.0 KB
05 - K-Nearest Neighbors/
001 K-Nearest Neighbors.mp4	32.1 MB
001 K-Nearest Neighbors.srt	10.0 KB
002 The KNN Workflow.mp4	21.6 MB
002 The KNN Workflow.srt	8.5 KB
003 KNN in Python.mp4	9.8 MB
003 KNN in Python.srt	3.6 KB
004 Model Accuracy.mp4	16.9 MB
004 Model Accuracy.srt	6.6 KB
005 Confusion Matrix.mp4	21.1 MB
005 Confusion Matrix.srt	7.2 KB
006 DEMO Confusion Matrix.mp4	24.4 MB
006 DEMO Confusion Matrix.srt	6.7 KB
007 ASSIGNMENT Fitting a Simple KNN Model.mp4	11.4 MB
007 ASSIGNMENT Fitting a Simple KNN Model.srt	3.1 KB
008 SOLUTION Fitting a Simple KNN Model.mp4	25.7 MB
008 SOLUTION Fitting a Simple KNN Model.srt	6.6 KB
009 Hyperparameter Tuning.mp4	7.7 MB
009 Hyperparameter Tuning.srt	6.2 KB
010 Overfitting & Validation.mp4	20.2 MB
010 Overfitting & Validation.srt	12.1 KB
011 DEMO Hyperparameter Tuning.mp4	16.5 MB
011 DEMO Hyperparameter Tuning.srt	10.3 KB
012 Hard vs. Soft Classification.mp4	14.8 MB
012 Hard vs. Soft Classification.srt	8.3 KB
013 DEMO Probability vs. Event Rate.mp4	35.2 MB
013 DEMO Probability vs. Event Rate.srt	16.8 KB
014 ASSIGNMENT Tuning a KNN Model.mp4	4.0 MB
014 ASSIGNMENT Tuning a KNN Model.srt	2.3 KB
015 SOLUTION Tuning a KNN Model.mp4	19.3 MB
015 SOLUTION Tuning a KNN Model.srt	5.6 KB
016 Pros & Cons of KNN.mp4	11.4 MB
016 Pros & Cons of KNN.srt	7.2 KB
017 Key Takeaways.mp4	2.5 MB
017 Key Takeaways.srt	2.1 KB
06 - Logistic Regression/
001 Logistic Regression.mp4	16.0 MB
001 Logistic Regression.srt	5.0 KB
002 Logistic vs. Linear Regression.mp4	12.6 MB
002 Logistic vs. Linear Regression.srt	4.3 KB
003 The Logistic Function.mp4	7.0 MB
003 The Logistic Function.srt	5.4 KB
004 Likelihood.mp4	11.1 MB
004 Likelihood.srt	8.2 KB
005 Multiple Logistic Regression.mp4	6.8 MB
005 Multiple Logistic Regression.srt	5.4 KB
006 The Logistic Regression Workflow.mp4	1.9 MB
006 The Logistic Regression Workflow.srt	1.6 KB
007 Logistic Regression in Python.mp4	15.9 MB
007 Logistic Regression in Python.srt	7.8 KB
008 Interpreting Coefficients.mp4	9.4 MB
008 Interpreting Coefficients.srt	5.8 KB
009 ASSIGNMENT Logistic Regression.mp4	7.9 MB
009 ASSIGNMENT Logistic Regression.srt	2.8 KB
010 SOLUTION Logistic Regression.mp4	9.9 MB
010 SOLUTION Logistic Regression.srt	5.8 KB
011 Feature Engineering & Selection.mp4	11.4 MB
011 Feature Engineering & Selection.srt	6.6 KB
012 Regularization.mp4	11.9 MB
012 Regularization.srt	9.4 KB
013 Tuning a Regularized Model.mp4	9.3 MB
013 Tuning a Regularized Model.srt	6.4 KB
014 DEMO Regularized Logistic Regression.mp4	24.0 MB
014 DEMO Regularized Logistic Regression.srt	6.2 KB
015 ASSIGNMENT Regularized Logistic Regression.mp4	5.4 MB
015 ASSIGNMENT Regularized Logistic Regression.srt	2.1 KB
016 SOLUTION Regularized Logistic Regression.mp4	45.7 MB
016 SOLUTION Regularized Logistic Regression.srt	7.3 KB
017 Multi-class Logistic Regression.mp4	16.2 MB
017 Multi-class Logistic Regression.srt	11.7 KB
018 ASSIGNMENT Multi-class Logistic Regression.mp4	4.4 MB
018 ASSIGNMENT Multi-class Logistic Regression.srt	2.6 KB
019 SOLUTION Multi-class Logistic Regression.mp4	9.7 MB
019 SOLUTION Multi-class Logistic Regression.srt	6.2 KB
020 Pros & Cons of Logistic Regression.mp4	6.9 MB
020 Pros & Cons of Logistic Regression.srt	4.4 KB
021 Key Takeaways.mp4	3.4 MB
021 Key Takeaways.srt	3.0 KB
07 - Classification Metrics/
001 Classification Metrics.mp4	5.8 MB
001 Classification Metrics.srt	4.4 KB
002 Accuracy, Precision & Recall.mp4	13.9 MB
002 Accuracy, Precision & Recall.srt	11.1 KB
003 DEMO Accuracy, Precision & Recall.mp4	19.9 MB
003 DEMO Accuracy, Precision & Recall.srt	8.9 KB
004 PRO TIP F1 Score.mp4	10.1 MB
004 PRO TIP F1 Score.srt	6.1 KB
005 ASSIGNMENT Model Metrics.mp4	3.1 MB
005 ASSIGNMENT Model Metrics.srt	1.9 KB
006 SOLUTION Model Metrics.mp4	11.5 MB
006 SOLUTION Model Metrics.srt	6.9 KB
007 Soft Classification.mp4	14.9 MB
007 Soft Classification.srt	11.7 KB
008 DEMO Leveraging Soft Classification.mp4	9.3 MB
008 DEMO Leveraging Soft Classification.srt	5.4 KB
009 PRO TIP Precision-Recall & F1 Curves.mp4	9.2 MB
009 PRO TIP Precision-Recall & F1 Curves.srt	6.3 KB
010 DEMO Plotting Precision-Recall & F1 Curves.mp4	24.6 MB
010 DEMO Plotting Precision-Recall & F1 Curves.srt	7.1 KB
011 The ROC Curve & AUC.mp4	8.2 MB
011 The ROC Curve & AUC.srt	5.0 KB
012 DEMO The ROC Curve & AUC.mp4	10.6 MB
012 DEMO The ROC Curve & AUC.srt	6.3 KB
013 Classification Metrics Recap.mp4	8.7 MB
013 Classification Metrics Recap.srt	4.1 KB
014 ASSIGNMENT Threshold Shifting.mp4	4.3 MB
014 ASSIGNMENT Threshold Shifting.srt	2.4 KB
015 SOLUTION Threshold Shifting.mp4	17.5 MB
015 SOLUTION Threshold Shifting.srt	9.7 KB
016 Multi-class Metrics.mp4	13.2 MB
016 Multi-class Metrics.srt	9.4 KB
017 Multi-class Metrics in Python.mp4	3.8 MB
017 Multi-class Metrics in Python.srt	2.8 KB
018 ASSIGNMENT Multi-class Metrics.mp4	3.0 MB
018 ASSIGNMENT Multi-class Metrics.srt	1.7 KB
019 SOLUTION Multi-class Metrics.mp4	10.0 MB
019 SOLUTION Multi-class Metrics.srt	4.7 KB
020 Key Takeaways.mp4	3.9 MB
020 Key Takeaways.srt	2.5 KB
08 - Imbalanced Data/
001 Imbalanced Data.mp4	10.0 MB
001 Imbalanced Data.srt	6.7 KB
002 Managing Imbalanced Data.mp4	22.3 MB
002 Managing Imbalanced Data.srt	7.0 KB
003 Threshold Shifting.mp4	5.6 MB
003 Threshold Shifting.srt	3.9 KB
004 Sampling Strategies.mp4	4.5 MB
004 Sampling Strategies.srt	3.2 KB
005 Oversampling.mp4	3.5 MB
005 Oversampling.srt	2.6 KB
006 Oversampling in Python.mp4	6.8 MB
006 Oversampling in Python.srt	4.6 KB
007 DEMO Oversampling.mp4	12.2 MB
007 DEMO Oversampling.srt	7.6 KB
008 SMOTE.mp4	2.6 MB
008 SMOTE.srt	2.1 KB
009 SMOTE in Python.mp4	6.4 MB
009 SMOTE in Python.srt	4.3 KB
010 Undersampling.mp4	4.9 MB
010 Undersampling.srt	3.8 KB
011 Undersampling in Python.mp4	16.2 MB
011 Undersampling in Python.srt	8.7 KB
012 ASSIGNMENT Sampling Methods.mp4	13.2 MB
012 ASSIGNMENT Sampling Methods.srt	4.1 KB
013 SOLUTION Sampling Methods.mp4	19.0 MB
013 SOLUTION Sampling Methods.srt	8.7 KB
014 Changing Class Weights.mp4	7.2 MB
014 Changing Class Weights.srt	4.5 KB
015 DEMO Changing Class Weights.mp4	9.6 MB
015 DEMO Changing Class Weights.srt	4.7 KB
016 ASSIGNMENT Changing Class Weights.mp4	2.4 MB
016 ASSIGNMENT Changing Class Weights.srt	2.1 KB
017 SOLUTION Changing Class Weights.mp4	11.0 MB
017 SOLUTION Changing Class Weights.srt	5.7 KB
018 Imbalanced Data Recap.mp4	3.6 MB
018 Imbalanced Data Recap.srt	3.4 KB
019 Key Takeaways.mp4	2.3 MB
019 Key Takeaways.srt	2.0 KB
09 - Mid-Course Project/
001 Project Brief.mp4	14.9 MB
001 Project Brief.srt	8.5 KB
002 Solution Walkthrough.mp4	56.4 MB
002 Solution Walkthrough.srt	19.5 KB
10 - Decision Trees/
001 Decision Trees.mp4	7.9 MB
001 Decision Trees.srt	6.6 KB
002 Entropy.mp4	12.1 MB
002 Entropy.srt	9.5 KB
003 Decision Tree Predictions.mp4	9.8 MB
003 Decision Tree Predictions.srt	7.4 KB
004 Decision Trees in Python.mp4	7.1 MB
004 Decision Trees in Python.srt	5.2 KB
005 DEMO Decision Trees.mp4	33.9 MB
005 DEMO Decision Trees.srt	6.4 KB
006 Feature Importance.mp4	15.8 MB
006 Feature Importance.srt	8.7 KB
007 ASSIGNMENT Decision Trees.mp4	3.5 MB
007 ASSIGNMENT Decision Trees.srt	2.5 KB
008 SOLUTION Decision Trees.mp4	31.4 MB
008 SOLUTION Decision Trees.srt	10.3 KB
009 Hyperparameter Tuning for Decision Trees.mp4	27.5 MB
009 Hyperparameter Tuning for Decision Trees.srt	7.7 KB
010 DEMO Hyperparameter Tuning.mp4	15.7 MB
010 DEMO Hyperparameter Tuning.srt	4.5 KB
011 ASSIGNMENT Tuned Decision Tree.mp4	2.1 MB
011 ASSIGNMENT Tuned Decision Tree.srt	1.6 KB
012 SOLUTION Tuned Decision Tree.mp4	15.4 MB
012 SOLUTION Tuned Decision Tree.srt	7.1 KB
013 Pros & Cons of Decision Trees.mp4	6.9 MB
013 Pros & Cons of Decision Trees.srt	4.5 KB
014 Key Takeaways.mp4	2.5 MB
014 Key Takeaways.srt	1.7 KB
11 - Ensemble Models/
001 Ensemble Models.mp4	9.2 MB
001 Ensemble Models.srt	6.6 KB
002 Simple Ensemble Models.mp4	5.4 MB
002 Simple Ensemble Models.srt	3.8 KB
003 DEMO Simple Ensemble Models.mp4	14.1 MB
003 DEMO Simple Ensemble Models.srt	5.8 KB
004 ASSIGNMENT Simple Ensemble Models.mp4	4.7 MB
004 ASSIGNMENT Simple Ensemble Models.srt	2.4 KB
005 SOLUTION Simple Ensemble Models.mp4	11.7 MB
005 SOLUTION Simple Ensemble Models.srt	5.3 KB
006 Random Forests.mp4	6.6 MB
006 Random Forests.srt	2.1 KB
007 Fitting Random Forests in Python.mp4	11.7 MB
007 Fitting Random Forests in Python.srt	7.0 KB
008 Hyperparameter Tuning for Random Forests.mp4	14.2 MB
008 Hyperparameter Tuning for Random Forests.srt	8.1 KB
009 PRO TIP Random Search.mp4	27.8 MB
009 PRO TIP Random Search.srt	8.8 KB
010 Pros & Cons of Random Forests.mp4	4.3 MB
011 ASSIGNMENT Random Forests.mp4	2.4 MB
011 ASSIGNMENT Random Forests.srt	2.2 KB
012 SOLUTION Random Forests.mp4	45.7 MB
012 SOLUTION Random Forests.srt	9.0 KB
013 Gradient Boosting.mp4	10.1 MB
013 Gradient Boosting.srt	3.9 KB
014 Gradient Boosting in Python.mp4	6.5 MB
014 Gradient Boosting in Python.srt	3.7 KB
015 Hyperparameter Tuning for Gradient Boosting.mp4	12.2 MB
015 Hyperparameter Tuning for Gradient Boosting.srt	8.3 KB
016 DEMO Hyperparameter Tuning for Gradient Boosting.mp4	24.0 MB
016 DEMO Hyperparameter Tuning for Gradient Boosting.srt	5.7 KB
017 Pros & Cons of Gradient Boosting.mp4	4.4 MB
017 Pros & Cons of Gradient Boosting.srt	3.0 KB
018 ASSIGNMENT Gradient Boosting.mp4	2.4 MB
018 ASSIGNMENT Gradient Boosting.srt	2.5 KB
019 SOLUTION Gradient Boosting.mp4	15.7 MB
019 SOLUTION Gradient Boosting.srt	7.0 KB
020 PRO TIP SHAP Values.mp4	17.4 MB
020 PRO TIP SHAP Values.srt	10.2 KB
021 DEMO SHAP Values.mp4	15.4 MB
021 DEMO SHAP Values.srt	8.6 KB
022 Key Takeaways.mp4	2.6 MB
022 Key Takeaways.srt	2.1 KB
12 - Classification Summary/
001 Recap Classification Models & Workflow.mp4	7.6 MB
001 Recap Classification Models & Workflow.srt	4.9 KB
002 Pros & Cons of Classification Models.mp4	8.8 MB
002 Pros & Cons of Classification Models.srt	5.2 KB
003 DEMO Production Pipeline & Deployment.mp4	58.4 MB
003 DEMO Production Pipeline & Deployment.srt	19.3 KB
004 Looking Ahead Unsupervised Learning.mp4	5.8 MB
004 Looking Ahead Unsupervised Learning.srt	1.8 KB
13 - Final Project/
001 Project Brief.mp4	14.7 MB
001 Project Brief.srt	4.7 KB
002 Solution Walkthrough.mp4	40.5 MB
002 Solution Walkthrough.srt	11.4 KB
14 - Next Steps/
001 BONUS LESSON.html	12.4 KB
Total files 338