Tutorialsplanet NET Udemy Python SQL Tableau Integrating Python SQL and Tableau

/1. Introduction/

1. What Does the Course Cover.mp4

1. What Does the Course Cover.srt

1.1 Course Resources - Complete Package.html

/10. Bonus lecture/

1. Bonus Lecture Next Steps.html

/2. What is software integration/

1. Properties and Definitions Data, Servers, Clients, Requests and Responses.mp4

1. Properties and Definitions Data, Servers, Clients, Requests and Responses.srt

10. Definitions and Applications.html

2. Properties and Definitions Data, Servers, Clients, Requests and Responses.html

3. Properties and Definitions Data Connectivity, APIs, and Endpoints.mp4

3. Properties and Definitions Data Connectivity, APIs, and Endpoints.srt

4. Properties and Definitions Data Connectivity, APIs, and Endpoints.html

5. Further Details on APIs.mp4

5. Further Details on APIs.srt

6. Further Details on APIs.html

7. Text Files as Means of Communication.mp4

7. Text Files as Means of Communication.srt

8. Text Files as Means of Communication.html

9. Definitions and Applications.mp4

9. Definitions and Applications.srt

/3. Setting up the working environment/

1. Setting Up the Environment - An Introduction (Do Not Skip, Please)!.mp4

1. Setting Up the Environment - An Introduction (Do Not Skip, Please)!.srt

10. Installing Packages - Exercise.html

11. Installing Packages - Solution.html

2. Why Python and why Jupyter.mp4

2. Why Python and why Jupyter.srt

3. Why Python and why Jupyter.html

4. Installing Anaconda.mp4

4. Installing Anaconda.srt

5. The Jupyter Dashboard - Part 1.mp4

5. The Jupyter Dashboard - Part 1.srt

6. The Jupyter Dashboard - Part 2.mp4

6. The Jupyter Dashboard - Part 2.srt

7. Jupyter Shortcuts.html

7.1 Shortcuts-for-Jupyter.pdf

8. The Jupyter Dashboard.html

9. Installing sklearn.mp4

9. Installing sklearn.srt

/4. What's next in the course/

1. Up Ahead.mp4

1. Up Ahead.srt

2. Real-Life Example Absenteeism at Work.mp4

2. Real-Life Example Absenteeism at Work.srt

3. Real-Life Example The Dataset.mp4

3. Real-Life Example The Dataset.srt

4. Real-Life Example The Dataset.html

5. Important Notice Regarding Datasets.html

/5. Preprocessing/

1. What to Expect from the Next Couple of Sections.html

1.1 df_preprocessed.csv

1.2 data_preprocessing_homework.pptx

1.3 Absenteeism_data.csv

10. Examining the Reasons for Absence.mp4

10. Examining the Reasons for Absence.srt

11. Splitting a Column into Multiple Dummies.mp4

11. Splitting a Column into Multiple Dummies.srt

12. EXERCISE - Splitting a Column into Multiple Dummies.html

13. SOLUTION - Splitting a Column into Multiple Dummies.html

14. ARTICLE - Dummy Variables Reasoning.html

15. Dummy Variables and Their Statistical Importance.mp4

15. Dummy Variables and Their Statistical Importance.srt

16. Grouping - Transforming Dummy Variables into Categorical Variables.mp4

16. Grouping - Transforming Dummy Variables into Categorical Variables.srt

17. Concatenating Columns in Python.mp4

17. Concatenating Columns in Python.srt

18. EXERCISE - Concatenating Columns in Python.html

19. SOLUTION - Concatenating Columns in Python.html

2. Data Sets in Python.mp4

2. Data Sets in Python.srt

20. Changing Column Order in Pandas DataFrame.mp4

20. Changing Column Order in Pandas DataFrame.srt

21. EXERCISE - Changing Column Order in Pandas DataFrame.html

22. SOLUTION - Changing Column Order in Pandas DataFrame.html

23. Implementing Checkpoints in Coding.mp4

23. Implementing Checkpoints in Coding.srt

23.1 Implementing Checkpoints in Coding.html

24. EXERCISE - Implementing Checkpoints in Coding.html

25. SOLUTION - Implementing Checkpoint in Coding.html

26. Exploring the Initial Date Column.mp4

26. Exploring the Initial Date Column.srt

27. Using the Date Column to Extract the Appropriate Month Value.mp4

27. Using the Date Column to Extract the Appropriate Month Value.srt

28. Introducing Day of the Week.mp4

28. Introducing Day of the Week.srt

29. EXERCISE - Removing Columns.html

29.1 Removing Columns.html

29.2 Preprocessing - df_reason_date_mod.html

3. Data at a Glance.mp4

3. Data at a Glance.srt

30. Further Analysis of the DataFrame Next 5 Columns.mp4

30. Further Analysis of the DataFrame Next 5 Columns.srt

31. Further Analysis of the DaraFrame Education, Children, Pets.mp4

31. Further Analysis of the DaraFrame Education, Children, Pets.srt

32. A Final Note on Preprocessing.mp4

32. A Final Note on Preprocessing.srt

32.1 Exercises and Solutions.html

32.2 Preprocessing - Lectures.html

32.3 Preprocessing - df_preprocessed.html

33. A Note on Exporting Your Data as a .csv File.html

4. A Note on Our Usage of Terms with Multiple Meanings.mp4

4. A Note on Our Usage of Terms with Multiple Meanings.srt

5. ARTICLE - A Brief Overview of Regression Analysis.html

6. Picking the Appropriate Approach for the Task at Hand.mp4

6. Picking the Appropriate Approach for the Task at Hand.srt

7. Removing Irrelevant Data.mp4

7. Removing Irrelevant Data.srt

8. EXERCISE - Removing Irrelevant Data.html

9. SOLUTION - Removing Irrelevant Data.html

/6. Machine Learning/

1. Exploring the Problem from a Machine Learning Point of View.mp4

1. Exploring the Problem from a Machine Learning Point of View.srt

1.1 Absenteeism_preprocessed.csv

10. Interpreting the Important Predictors.mp4

10. Interpreting the Important Predictors.srt

11. Simplifying the Model (Backward Elimination).mp4

11. Simplifying the Model (Backward Elimination).srt

11.1 Logistic Regression prior to Backward Elimination.html

12. Testing the Machine Learning Model.mp4

12. Testing the Machine Learning Model.srt

13. How to Save the Machine Learning Model and Prepare it for Future Deployment.mp4

13. How to Save the Machine Learning Model and Prepare it for Future Deployment.srt

14. ARTICLE - More about 'pickling'.html

15. EXERCISE - Saving the Model (and Scaler).html

15.1 Logistic Regression with Comments.html

15.2 Logistic Regression.html

16. Creating a Module for Later Use of the Model.mp4

16. Creating a Module for Later Use of the Model.srt

2. Creating the Targets for the Logistic Regression.mp4

2. Creating the Targets for the Logistic Regression.srt

3. Selecting the Inputs.mp4

3. Selecting the Inputs.srt

4. A Bit of Statistical Preprocessing.mp4

4. A Bit of Statistical Preprocessing.srt

5. Train-test Split of the Data.mp4

5. Train-test Split of the Data.srt

6. Training the Model and Assessing its Accuracy.mp4

6. Training the Model and Assessing its Accuracy.srt

7. Extracting the Intercept and Coefficients from a Logistic Regression.mp4

7. Extracting the Intercept and Coefficients from a Logistic Regression.srt

8. Interpreting the Logistic Regression Coefficients.mp4

8. Interpreting the Logistic Regression Coefficients.srt

9. Omitting the dummy variables from the Standardization.mp4

9. Omitting the dummy variables from the Standardization.srt

9.1 Logistic Regression prior to Custom Scaler.html

/7. Installing MySQL and Getting Acquainted with the Interface/

1. Installing MySQL.mp4

1. Installing MySQL.srt

2. Installing MySQL on macOS and Unix systems.html

3. Setting Up a Connection.mp4

3. Setting Up a Connection.srt

4. Introduction to the MySQL Interface.mp4

4. Introduction to the MySQL Interface.srt

/8. Connecting Python and SQL/

1. Are you sure you're all set.html

1.1 5 Files Needed to Deploy the Model.html

10. Transferring Data from Jupyter to Workbench - Part I.mp4

10. Transferring Data from Jupyter to Workbench - Part I.srt

11. Transferring Data from Jupyter to Workbench - Part II.mp4

11. Transferring Data from Jupyter to Workbench - Part II.srt

12. Transferring Data from Jupyter to Workbench - Part III.mp4

12. Transferring Data from Jupyter to Workbench - Part III.srt

12.1 Integration.html

2. Implementing the 'absenteeism_module' - Part I.mp4

2. Implementing the 'absenteeism_module' - Part I.srt

3. Implementing the 'absenteeism_module' - Part II.mp4

3. Implementing the 'absenteeism_module' - Part II.srt

4. Creating a Database in MySQL.mp4

4. Creating a Database in MySQL.srt

5. Importing and Installing 'pymysql'.mp4

5. Importing and Installing 'pymysql'.srt

6. Creating a Connection and Cursor.mp4

6. Creating a Connection and Cursor.srt

7. EXERCISE - Create 'df_new_obs'.html

8. Creating the 'predicted_outputs' table in MySQL.mp4

8. Creating the 'predicted_outputs' table in MySQL.srt

9. Running an SQL SELECT Statement from Python.mp4

9. Running an SQL SELECT Statement from Python.srt

/9. Analyzing the Obtained data in Tableau/

1. EXERCISE - Age vs Probability.html

2. Analysis in Tableau Age vs Probability.mp4

2. Analysis in Tableau Age vs Probability.srt

3. EXERCISE - Reasons vs Probability.html

4. Analysis in Tableau Reasons vs Probability.mp4

4. Analysis in Tableau Reasons vs Probability.srt

5. EXERCISE - Transportation Expense vs Probability.html

6. Analysis in Tableau Transportation Expense vs Probability.mp4

6. Analysis in Tableau Transportation Expense vs Probability.srt

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