|
|
001 Course Introduction.en.srt
|
SRT
|
2.8 KB
|
|
|
001 Course Introduction.mp4
|
MP4
|
22.6 MB
|
|
|
001 Curse of Dimensionality.en.srt
|
SRT
|
2.7 KB
|
|
|
001 Curse of Dimensionality.mp4
|
MP4
|
6.2 MB
|
|
|
001 Data Cleansing Overview.en.srt
|
SRT
|
2.2 KB
|
|
|
001 Data Cleansing Overview.mp4
|
MP4
|
20 MB
|
|
|
001 Feature Selection Introduction.en.srt
|
SRT
|
2.4 KB
|
|
|
001 Feature Selection Introduction.mp4
|
MP4
|
19.5 MB
|
|
|
001 Introducing Data Preparation.en.srt
|
SRT
|
2.8 KB
|
|
|
001 Introducing Data Preparation.mp4
|
MP4
|
36.4 MB
|
|
|
001 Scale Numerical Data.en.srt
|
SRT
|
2.7 KB
|
|
|
001 Scale Numerical Data.mp4
|
MP4
|
5.1 MB
|
|
|
001 Transforming Different Data Types.en.srt
|
SRT
|
3.1 KB
|
|
|
001 Transforming Different Data Types.mp4
|
MP4
|
8.9 MB
|
|
|
002 Course Structure.en.srt
|
SRT
|
3.6 KB
|
|
|
002 Course Structure.mp4
|
MP4
|
23.9 MB
|
|
|
002 Diabetes Dataset for Scaling.en.srt
|
SRT
|
2.5 KB
|
|
|
002 Diabetes Dataset for Scaling.mp4
|
MP4
|
8.7 MB
|
|
|
002 Feature Selection Defined.en.srt
|
SRT
|
4.4 KB
|
|
|
002 Feature Selection Defined.mp4
|
MP4
|
5.2 MB
|
|
|
002 Identify Columns That Contain a Single Value.en.srt
|
SRT
|
3.2 KB
|
|
|
002 Identify Columns That Contain a Single Value.mp4
|
MP4
|
7.5 MB
|
|
|
002 Techniques for Dimensionality Reduction.en.srt
|
SRT
|
4.9 KB
|
|
|
002 Techniques for Dimensionality Reduction.mp4
|
MP4
|
13 MB
|
|
|
002 The ColumnTransformer.en.srt
|
SRT
|
3.1 KB
|
|
|
002 The ColumnTransformer.mp4
|
MP4
|
10.5 MB
|
|
|
002 The Machine Learning Process.en.srt
|
SRT
|
5.4 KB
|
|
|
002 The Machine Learning Process.mp4
|
MP4
|
14.3 MB
|
|
|
003 Data Preparation Defined.en.srt
|
SRT
|
3.8 KB
|
|
|
003 Data Preparation Defined.mp4
|
MP4
|
30.2 MB
|
|
|
003 Identify Columns with Few Values.en.srt
|
SRT
|
4.2 KB
|
|
|
003 Identify Columns with Few Values.mp4
|
MP4
|
12 MB
|
|
|
003 Is this Course Right for You_.en.srt
|
SRT
|
1.7 KB
|
|
|
003 Is this Course Right for You_.mp4
|
MP4
|
1.6 MB
|
|
|
003 Linear Discriminant Analysis.en.srt
|
SRT
|
3 KB
|
|
|
003 Linear Discriminant Analysis.mp4
|
MP4
|
7.6 MB
|
|
|
003 MinMaxScaler Transform.en.srt
|
SRT
|
2.3 KB
|
|
|
003 MinMaxScaler Transform.mp4
|
MP4
|
8.9 MB
|
|
|
003 Statistics for Feature Selection.en.srt
|
SRT
|
3 KB
|
|
|
003 Statistics for Feature Selection.mp4
|
MP4
|
9.5 MB
|
|
|
003 The ColumnTransformer on Abalone Dataset.en.srt
|
SRT
|
3.7 KB
|
|
|
003 The ColumnTransformer on Abalone Dataset.mp4
|
MP4
|
13.1 MB
|
|
|
004 Choosing a Data Preparation Technique.en.srt
|
SRT
|
2.7 KB
|
|
|
004 Choosing a Data Preparation Technique.mp4
|
MP4
|
25.9 MB
|
|
|
004 Linear Discriminant Analysis Demonstrated.en.srt
|
SRT
|
5.3 KB
|
|
|
004 Linear Discriminant Analysis Demonstrated.mp4
|
MP4
|
18.6 MB
|
|
|
004 Loading a Categorical Dataset.en.srt
|
SRT
|
3.4 KB
|
|
|
004 Loading a Categorical Dataset.mp4
|
MP4
|
10.3 MB
|
|
|
004 Manually Transform Target Variable.en.srt
|
SRT
|
3.4 KB
|
|
|
004 Manually Transform Target Variable.mp4
|
MP4
|
13.2 MB
|
|
|
004 Remove Columns with Low Variance.en.srt
|
SRT
|
3.8 KB
|
|
|
004 Remove Columns with Low Variance.mp4
|
MP4
|
11.2 MB
|
|
|
004 StandardScaler Transform.en.srt
|
SRT
|
2.6 KB
|
|
|
004 StandardScaler Transform.mp4
|
MP4
|
10.5 MB
|
|
|
005 Automatically Transform Target Variable.en.srt
|
SRT
|
5.4 KB
|
|
|
005 Automatically Transform Target Variable.mp4
|
MP4
|
20.4 MB
|
|
|
005 Encode the Dataset for Modeling.en.srt
|
SRT
|
3.1 KB
|
|
|
005 Encode the Dataset for Modeling.mp4
|
MP4
|
9.4 MB
|
|
|
005 Identify and Remove Rows That Contain Duplicate Data.en.srt
|
SRT
|
3.9 KB
|
|
|
005 Identify and Remove Rows That Contain Duplicate Data.mp4
|
MP4
|
15.6 MB
|
|
|
005 Principal Component Analysis.en.srt
|
SRT
|
7.2 KB
|
|
|
005 Principal Component Analysis.mp4
|
MP4
|
22.6 MB
|
|
|
005 Robust Scaling Data.en.srt
|
SRT
|
5.6 KB
|
|
|
005 Robust Scaling Data.mp4
|
MP4
|
16.5 MB
|
|
|
005 What is Data in Machine Learning_.en.srt
|
SRT
|
4.7 KB
|
|
|
005 What is Data in Machine Learning_.mp4
|
MP4
|
17.9 MB
|
|
|
006 Challenge of Preparing New Data for a Model.en.srt
|
SRT
|
4.9 KB
|
|
|
006 Challenge of Preparing New Data for a Model.mp4
|
MP4
|
34.1 MB
|
|
|
006 Chi-Squared.en.srt
|
SRT
|
3 KB
|
|
|
006 Chi-Squared.mp4
|
MP4
|
7 MB
|
|
|
006 Defining Outliers.en.srt
|
SRT
|
2.7 KB
|
|
|
006 Defining Outliers.mp4
|
MP4
|
14.4 MB
|
|
|
006 Raw Data.en.srt
|
SRT
|
8.2 KB
|
|
|
006 Raw Data.mp4
|
MP4
|
20.5 MB
|
|
|
006 Robust Scaler Applied to Dataset.en.srt
|
SRT
|
2.2 KB
|
|
|
006 Robust Scaler Applied to Dataset.mp4
|
MP4
|
8.4 MB
|
|
|
007 Explore Robust Scaler Range.en.srt
|
SRT
|
1.6 KB
|
|
|
007 Explore Robust Scaler Range.mp4
|
MP4
|
5.6 MB
|
|
|
007 Machine Learning is Mostly Data Preparation.en.srt
|
SRT
|
4.1 KB
|
|
|
007 Machine Learning is Mostly Data Preparation.mp4
|
MP4
|
40.9 MB
|
|
|
007 Mutual Information.en.srt
|
SRT
|
2.2 KB
|
|
|
007 Mutual Information.mp4
|
MP4
|
6.9 MB
|
|
|
007 Remove Outliers - The Standard Deviation Approach.en.srt
|
SRT
|
5.4 KB
|
|
|
007 Remove Outliers - The Standard Deviation Approach.mp4
|
MP4
|
18.5 MB
|
|
|
007 Save Model and Data Scaler.en.srt
|
SRT
|
3.8 KB
|
|
|
007 Save Model and Data Scaler.mp4
|
MP4
|
15.2 MB
|
|
|
008 Common Data Preparation Tasks - Data Cleansing.en.srt
|
SRT
|
3.7 KB
|
|
|
008 Common Data Preparation Tasks - Data Cleansing.mp4
|
MP4
|
21.7 MB
|
|
|
008 Load and Apply Saved Scalers.en.srt
|
SRT
|
2 KB
|
|
|
008 Load and Apply Saved Scalers.mp4
|
MP4
|
6.6 MB
|
|
|
008 Modeling with Selected Categorical Features.en.srt
|
SRT
|
4 KB
|
|
|
008 Modeling with Selected Categorical Features.mp4
|
MP4
|
14.1 MB
|
|
|
008 Nominal and Ordinal Variables.en.srt
|
SRT
|
4.4 KB
|
|
|
008 Nominal and Ordinal Variables.mp4
|
MP4
|
26 MB
|
|
|
008 Remove Outliers - The IQR Approach.en.srt
|
SRT
|
3.8 KB
|
|
|
008 Remove Outliers - The IQR Approach.mp4
|
MP4
|
14.9 MB
|
|
|
009 Automatic Outlier Detection.en.srt
|
SRT
|
5.2 KB
|
|
|
009 Automatic Outlier Detection.mp4
|
MP4
|
18.6 MB
|
|
|
009 Common Data Preparation Tasks - Feature Selection.en.srt
|
SRT
|
3.5 KB
|
|
|
009 Common Data Preparation Tasks - Feature Selection.mp4
|
MP4
|
7.9 MB
|
|
|
009 Feature Selection with ANOVA on Numerical Input.en.srt
|
SRT
|
6.4 KB
|
|
|
009 Feature Selection with ANOVA on Numerical Input.mp4
|
MP4
|
17.2 MB
|
|
|
009 Ordinal Encoding.en.srt
|
SRT
|
3.3 KB
|
|
|
009 Ordinal Encoding.mp4
|
MP4
|
7 MB
|
|
|
010 Common Data Preparation Tasks - Data Transforms.en.srt
|
SRT
|
3.9 KB
|
|
|
010 Common Data Preparation Tasks - Data Transforms.mp4
|
MP4
|
4.7 MB
|
|
|
010 Feature Selection with Mutual Information.en.srt
|
SRT
|
2.7 KB
|
|
|
010 Feature Selection with Mutual Information.mp4
|
MP4
|
7.3 MB
|
|
|
010 Mark Missing Values.en.srt
|
SRT
|
6.8 KB
|
|
|
010 Mark Missing Values.mp4
|
MP4
|
22.7 MB
|
|
|
010 One-Hot Encoding Defined.en.srt
|
SRT
|
1.3 KB
|
|
|
010 One-Hot Encoding Defined.mp4
|
MP4
|
1.7 MB
|
|
|
011 Common Data Preparation Tasks - Feature Engineering.en.srt
|
SRT
|
2.2 KB
|
|
|
011 Common Data Preparation Tasks - Feature Engineering.mp4
|
MP4
|
21.6 MB
|
|
|
011 Modeling with Selected Numerical Features.en.srt
|
SRT
|
2.6 KB
|
|
|
011 Modeling with Selected Numerical Features.mp4
|
MP4
|
9.7 MB
|
|
|
011 One-Hot Encoding.en.srt
|
SRT
|
2.9 KB
|
|
|
011 One-Hot Encoding.mp4
|
MP4
|
6.8 MB
|
|
|
011 Remove Rows with Missing Values.en.srt
|
SRT
|
2.4 KB
|
|
|
011 Remove Rows with Missing Values.mp4
|
MP4
|
10 MB
|
|
|
012 Common Data Preparation Tasks - Dimensionality Reduction.en.srt
|
SRT
|
2.9 KB
|
|
|
012 Common Data Preparation Tasks - Dimensionality Reduction.mp4
|
MP4
|
4.1 MB
|
|
|
012 Dummy Variable Encoding.en.srt
|
SRT
|
3.1 KB
|
|
|
012 Dummy Variable Encoding.mp4
|
MP4
|
7 MB
|
|
|
012 Statistical Imputation.en.srt
|
SRT
|
2 KB
|
|
|
012 Statistical Imputation.mp4
|
MP4
|
2.6 MB
|
|
|
012 Tuning Number of Selected Features.en.srt
|
SRT
|
3.9 KB
|
|
|
012 Tuning Number of Selected Features.mp4
|
MP4
|
14.4 MB
|
|
|
013 Data Leakage.en.srt
|
SRT
|
1.1 KB
|
|
|
013 Data Leakage.mp4
|
MP4
|
8.8 MB
|
|
|
013 Mean Value Imputation.en.srt
|
SRT
|
4.9 KB
|
|
|
013 Mean Value Imputation.mp4
|
MP4
|
15.9 MB
|
|
|
013 OrdinalEncoder Transform on Breast Cancer Dataset.en.srt
|
SRT
|
5 KB
|
|
|
013 OrdinalEncoder Transform on Breast Cancer Dataset.mp4
|
MP4
|
17.1 MB
|
|
|
013 Select Features for Numerical Output.en.srt
|
SRT
|
3.4 KB
|
|
|
013 Select Features for Numerical Output.mp4
|
MP4
|
8.7 MB
|
|
|
014 Linear Correlation with Correlation Statistics.en.srt
|
SRT
|
3.3 KB
|
|
|
014 Linear Correlation with Correlation Statistics.mp4
|
MP4
|
9.9 MB
|
|
|
014 Make Distributions More Gaussian.en.srt
|
SRT
|
2.9 KB
|
|
|
014 Make Distributions More Gaussian.mp4
|
MP4
|
4 MB
|
|
|
014 Problem With Naïve Data Preparation.en.srt
|
SRT
|
5.2 KB
|
|
|
014 Problem With Naïve Data Preparation.mp4
|
MP4
|
24.9 MB
|
|
|
014 Simple Imputer with Model Evaluation.en.srt
|
SRT
|
1.8 KB
|
|
|
014 Simple Imputer with Model Evaluation.mp4
|
MP4
|
7.6 MB
|
|
|
015 Case Study_ Data Leakage_ Train_Test_Split Naïve Approach.en.srt
|
SRT
|
3.9 KB
|
|
|
015 Case Study_ Data Leakage_ Train_Test_Split Naïve Approach.mp4
|
MP4
|
16.5 MB
|
|
|
015 Compare Different Statistical Imputation Strategies.en.srt
|
SRT
|
2.5 KB
|
|
|
015 Compare Different Statistical Imputation Strategies.mp4
|
MP4
|
9.3 MB
|
|
|
015 Linear Correlation with Mutual Information.en.srt
|
SRT
|
3.1 KB
|
|
|
015 Linear Correlation with Mutual Information.mp4
|
MP4
|
10.8 MB
|
|
|
015 Power Transform on Contrived Dataset.en.srt
|
SRT
|
3.6 KB
|
|
|
015 Power Transform on Contrived Dataset.mp4
|
MP4
|
8.5 MB
|
|
|
016 Baseline and Model Built Using Correlation.en.srt
|
SRT
|
3.1 KB
|
|
|
016 Baseline and Model Built Using Correlation.mp4
|
MP4
|
13.1 MB
|
|
|
016 Case Study_ Data Leakage_ Train_Test_Split Correct Approach.en.srt
|
SRT
|
2.4 KB
|
|
|
016 Case Study_ Data Leakage_ Train_Test_Split Correct Approach.mp4
|
MP4
|
9.5 MB
|
|
|
016 K-Nearest Neighbors Imputation.en.srt
|
SRT
|
5.1 KB
|
|
|
016 K-Nearest Neighbors Imputation.mp4
|
MP4
|
16.9 MB
|
|
|
016 Power Transform on Sonar Dataset.en.srt
|
SRT
|
2.9 KB
|
|
|
016 Power Transform on Sonar Dataset.mp4
|
MP4
|
10.9 MB
|
|
|
017 Box-Cox on Sonar Dataset.en.srt
|
SRT
|
3.1 KB
|
|
|
017 Box-Cox on Sonar Dataset.mp4
|
MP4
|
11.7 MB
|
|
|
017 Case Study_ Data Leakage_ K-Fold Naïve Approach.en.srt
|
SRT
|
4.2 KB
|
|
|
017 Case Study_ Data Leakage_ K-Fold Naïve Approach.mp4
|
MP4
|
14.3 MB
|
|
|
017 KNNImputer and Model Evaluation.en.srt
|
SRT
|
3.4 KB
|
|
|
017 KNNImputer and Model Evaluation.mp4
|
MP4
|
12.9 MB
|
|
|
017 Model Built Using Mutual Information Features.en.srt
|
SRT
|
1 KB
|
|
|
017 Model Built Using Mutual Information Features.mp4
|
MP4
|
3.9 MB
|
|
|
018 Case Study_ Data Leakage_ K-Fold Correct Approach.en.srt
|
SRT
|
3.1 KB
|
|
|
018 Case Study_ Data Leakage_ K-Fold Correct Approach.mp4
|
MP4
|
12.8 MB
|
|
|
018 Iterative Imputation.en.srt
|
SRT
|
4.1 KB
|
|
|
018 Iterative Imputation.mp4
|
MP4
|
13.8 MB
|
|
|
018 Tuning Number of Selected Features.en.srt
|
SRT
|
4.8 KB
|
|
|
018 Tuning Number of Selected Features.mp4
|
MP4
|
20.3 MB
|
|
|
018 Yeo-Johnson on Sonar Dataset.en.srt
|
SRT
|
2.7 KB
|
|
|
018 Yeo-Johnson on Sonar Dataset.mp4
|
MP4
|
9.6 MB
|
|
|
019 IterativeImputer and Model Evaluation.en.srt
|
SRT
|
1.4 KB
|
|
|
019 IterativeImputer and Model Evaluation.mp4
|
MP4
|
6.5 MB
|
|
|
019 Polynomial Features.en.srt
|
SRT
|
5.2 KB
|
|
|
019 Polynomial Features.mp4
|
MP4
|
20.7 MB
|
|
|
019 Recursive Feature Elimination.en.srt
|
SRT
|
3.8 KB
|
|
|
019 Recursive Feature Elimination.mp4
|
MP4
|
27.9 MB
|
|
|
020 IterativeImputer and Different Imputation Order.en.srt
|
SRT
|
2.2 KB
|
|
|
020 IterativeImputer and Different Imputation Order.mp4
|
MP4
|
8.4 MB
|
|
|
020 Polynomial Transform on Sonar Dataset.en.srt
|
SRT
|
5.2 KB
|
|
|
020 Polynomial Transform on Sonar Dataset.mp4
|
MP4
|
20.6 MB
|
|
|
020 RFE for Classification.en.srt
|
SRT
|
4.6 KB
|
|
|
020 RFE for Classification.mp4
|
MP4
|
18.5 MB
|
|
|
021 Effect of Polynomial Degrees.en.srt
|
SRT
|
2.7 KB
|
|
|
021 Effect of Polynomial Degrees.mp4
|
MP4
|
7.5 MB
|
|
|
021 RFE for Regression.en.srt
|
SRT
|
2.6 KB
|
|
|
021 RFE for Regression.mp4
|
MP4
|
9.4 MB
|
|
|
022 RFE Hyperparameters.en.srt
|
SRT
|
3.4 KB
|
|
|
022 RFE Hyperparameters.mp4
|
MP4
|
12.1 MB
|
|
|
023 Feature Ranking for RFE.en.srt
|
SRT
|
3 KB
|
|
|
023 Feature Ranking for RFE.mp4
|
MP4
|
10.9 MB
|
|
|
024 Feature Importance Scores Defined.en.srt
|
SRT
|
3.9 KB
|
|
|
024 Feature Importance Scores Defined.mp4
|
MP4
|
26.2 MB
|
|
|
025 Feature Importance Scores_ Linear Regression.en.srt
|
SRT
|
4.3 KB
|
|
|
025 Feature Importance Scores_ Linear Regression.mp4
|
MP4
|
13.3 MB
|
|
|
026 Feature Importance Scores_ Logistic Regression and CART.en.srt
|
SRT
|
4.4 KB
|
|
|
026 Feature Importance Scores_ Logistic Regression and CART.mp4
|
MP4
|
14.2 MB
|
|
|
027 Feature Importance Scores_ Random Forests.en.srt
|
SRT
|
1.9 KB
|
|
|
027 Feature Importance Scores_ Random Forests.mp4
|
MP4
|
6.6 MB
|
|
|
028 Permutation Feature Importance.en.srt
|
SRT
|
3.1 KB
|
|
|
028 Permutation Feature Importance.mp4
|
MP4
|
10.8 MB
|
|
|
029 Feature Selection with Importance.en.srt
|
SRT
|
4.4 KB
|
|
|
029 Feature Selection with Importance.mp4
|
MP4
|
15.5 MB
|
|
|
030 housing.csv
|
CSV
|
47.9 KB
|
|
|
094 abalone.csv
|
CSV
|
187.4 KB
|
|
|
Advanced Transforms.ipynb
|
IPYNB
|
47.8 KB
|
|
|
Automatic Outlier Detection.ipynb
|
IPYNB
|
4.5 KB
|
|
|
Bonus Resources.txt
|
TXT
|
307.2 B
|
|
|
Categorical Feature Selection.ipynb
|
IPYNB
|
28.8 KB
|
|
|
Choosing Numerical Input Features.ipynb
|
IPYNB
|
36.7 KB
|
|
|
Comparing Different Imputed Statistics.ipynb
|
IPYNB
|
12.3 KB
|
|
|
Data Cleansing Master Class - Data Preparation With Training and Testing Sets.ipynb
|
IPYNB
|
6.6 KB
|
|
|
Data Rescaling .ipynb
|
IPYNB
|
60.4 KB
|
|
|
Dimensionality Reduction.ipynb
|
IPYNB
|
34.8 KB
|
|
|
Feature Importance Scores.ipynb
|
IPYNB
|
57.8 KB
|
|
|
Get Bonus Downloads Here.url
|
URL
|
204.8 B
|
|
|
Identify and Remove Duplicate Rows.ipynb
|
IPYNB
|
1.8 KB
|
|
|
IterativeImputer Data Transform.ipynb
|
IPYNB
|
2.4 KB
|
|
|
IterativeImputer and Different Number of Iterations.ipynb
|
IPYNB
|
14.1 KB
|
|
|
IterativeImputer and Model Evaluation.ipynb
|
IPYNB
|
2.4 KB
|
|
|
KNNImputer and Model Evaluation Different K-Values.ipynb
|
IPYNB
|
13.6 KB
|
|
|
Mark Missing Values.ipynb
|
IPYNB
|
11.3 KB
|
|
|
Outlier Removal - IQR Approach.ipynb
|
IPYNB
|
1.8 KB
|
|
|
Outlier Removal - Standard Deviation Approach.ipynb
|
IPYNB
|
2.3 KB
|
|
|
Polynomial Feature Transform.ipynb
|
IPYNB
|
26.9 KB
|
|
|
Power Transforms.ipynb
|
IPYNB
|
85.1 KB
|
|
|
Remove Missing Values.ipynb
|
IPYNB
|
9.4 KB
|
|
|
Select Features for Numerical Output.ipynb
|
IPYNB
|
44.1 KB
|
|
|
SimpleImputer and Model Evaluation.ipynb
|
IPYNB
|
2 KB
|
|
|
Sparse Column Identification and Removal.ipynb
|
IPYNB
|
20.6 KB
|
|
|
Statistical Imputation With KNN.ipynb
|
IPYNB
|
7.2 KB
|
|
|
Statistical Imputation With SimpleImputer.ipynb
|
IPYNB
|
7.2 KB
|
![[ FreeCourseWeb ] Udemy - Data Cleansing Master Class in Python](/static/img/no-torrent-image.png "[ FreeCourseWeb ] Udemy - Data Cleansing Master Class in Python")
