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[Tutorialsplanet.NET] Udemy - Python + SQL + Tableau Integrating Python, SQL, and Tableau
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文档列表
2. What is software integration/5. Further Details on APIs.mp4
121.3 MB
2. What is software integration/3. Properties and Definitions Data Connectivity, APIs, and Endpoints.mp4
109.3 MB
5. Preprocessing/30. Further Analysis of the DataFrame Next 5 Columns.srt
88.3 MB
5. Preprocessing/11. Splitting a Column into Multiple Dummies.mp4
85.0 MB
7. Installing MySQL and Getting Acquainted with the Interface/1. Installing MySQL.mp4
84.9 MB
8. Connecting Python and SQL/10. Transferring Data from Jupyter to Workbench - Part I.mp4
79.9 MB
5. Preprocessing/16. Grouping - Transforming Dummy Variables into Categorical Variables.mp4
78.2 MB
2. What is software integration/1. Properties and Definitions Data, Servers, Clients, Requests and Responses.mp4
72.5 MB
2. What is software integration/9. Definitions and Applications.mp4
66.8 MB
5. Preprocessing/3. Data at a Glance.mp4
64.8 MB
5. Preprocessing/7. Removing Irrelevant Data.mp4
64.7 MB
2. What is software integration/7. Text Files as Means of Communication.mp4
63.4 MB
9. Analyzing the Obtained data in Tableau/4. Analysis in Tableau Reasons vs Probability.mp4
62.2 MB
8. Connecting Python and SQL/4. Creating a Database in MySQL.mp4
61.8 MB
8. Connecting Python and SQL/11. Transferring Data from Jupyter to Workbench - Part II.mp4
61.1 MB
5. Preprocessing/26. Exploring the Initial Date Column.mp4
60.1 MB
9. Analyzing the Obtained data in Tableau/2. Analysis in Tableau Age vs Probability.mp4
59.2 MB
1. Introduction/1. What Does the Course Cover.mp4
58.9 MB
8. Connecting Python and SQL/3. Implementing the 'absenteeism_module' - Part II.mp4
56.9 MB
6. Machine Learning/5. Train-test Split of the Data.mp4
55.3 MB
8. Connecting Python and SQL/8. Creating the 'predicted_outputs' table in MySQL.mp4
55.0 MB
6. Machine Learning/8. Interpreting the Logistic Regression Coefficients.mp4
54.9 MB
4. What's next in the course/1. Up Ahead.mp4
54.9 MB
3. Setting up the working environment/4. Installing Anaconda.mp4
53.5 MB
6. Machine Learning/12. Testing the Machine Learning Model.mp4
51.5 MB
5. Preprocessing/27. Using the Date Column to Extract the Appropriate Month Value.mp4
50.1 MB
6. Machine Learning/2. Creating the Targets for the Logistic Regression.mp4
48.1 MB
6. Machine Learning/16. Creating a Module for Later Use of the Model.mp4
46.7 MB
6. Machine Learning/6. Training the Model and Assessing its Accuracy.mp4
43.7 MB
6. Machine Learning/9. Omitting the dummy variables from the Standardization.mp4
43.2 MB
3. Setting up the working environment/2. Why Python and why Jupyter.mp4
43.1 MB
4. What's next in the course/3. Real-Life Example The Dataset.mp4
42.9 MB
9. Analyzing the Obtained data in Tableau/6. Analysis in Tableau Transportation Expense vs Probability.mp4
42.6 MB
5. Preprocessing/10. Examining the Reasons for Absence.mp4
42.6 MB
6. Machine Learning/10. Interpreting the Important Predictors.mp4
42.4 MB
6. Machine Learning/11. Simplifying the Model (Backward Elimination).mp4
41.5 MB
5. Preprocessing/31. Further Analysis of the DaraFrame Education, Children, Pets.mp4
41.5 MB
4. What's next in the course/2. Real-Life Example Absenteeism at Work.mp4
41.1 MB
6. Machine Learning/7. Extracting the Intercept and Coefficients from a Logistic Regression.mp4
40.7 MB
5. Preprocessing/17. Concatenating Columns in Python.mp4
40.6 MB
6. Machine Learning/13. How to Save the Machine Learning Model and Prepare it for Future Deployment.mp4
39.3 MB
7. Installing MySQL and Getting Acquainted with the Interface/4. Introduction to the MySQL Interface.mp4
39.0 MB
7. Installing MySQL and Getting Acquainted with the Interface/4. Introduction to the MySQL Interface.srt
36.6 MB
8. Connecting Python and SQL/12. Transferring Data from Jupyter to Workbench - Part III.mp4
34.4 MB
5. Preprocessing/30. Further Analysis of the DataFrame Next 5 Columns.mp4
31.0 MB
3. Setting up the working environment/6. The Jupyter Dashboard - Part 2.mp4
30.0 MB
5. Preprocessing/28. Introducing Day of the Week.mp4
29.4 MB
5. Preprocessing/4. A Note on Our Usage of Terms with Multiple Meanings.mp4
29.3 MB
6. Machine Learning/1. Exploring the Problem from a Machine Learning Point of View.mp4
28.8 MB
5. Preprocessing/23. Implementing Checkpoints in Coding.mp4
27.0 MB
8. Connecting Python and SQL/2. Implementing the 'absenteeism_module' - Part I.mp4
26.7 MB
8. Connecting Python and SQL/9. Running an SQL SELECT Statement from Python.mp4
26.7 MB
5. Preprocessing/2. Data Sets in Python.mp4
24.3 MB
5. Preprocessing/32. A Final Note on Preprocessing.mp4
22.7 MB
8. Connecting Python and SQL/6. Creating a Connection and Cursor.mp4
22.0 MB
6. Machine Learning/4. A Bit of Statistical Preprocessing.mp4
21.6 MB
5. Preprocessing/6. Picking the Appropriate Approach for the Task at Hand.mp4
21.2 MB
8. Connecting Python and SQL/5. Importing and Installing 'pymysql'.mp4
20.0 MB
7. Installing MySQL and Getting Acquainted with the Interface/3. Setting Up a Connection.mp4
18.4 MB
6. Machine Learning/3. Selecting the Inputs.mp4
17.6 MB
5. Preprocessing/20. Changing Column Order in Pandas DataFrame.mp4
14.7 MB
5. Preprocessing/15. Dummy Variables and Their Statistical Importance.mp4
14.5 MB
3. Setting up the working environment/5. The Jupyter Dashboard - Part 1.mp4
14.1 MB
3. Setting up the working environment/9. Installing sklearn.mp4
8.1 MB
3. Setting up the working environment/1. Setting Up the Environment - An Introduction (Do Not Skip, Please)!.mp4
5.6 MB
3. Setting up the working environment/7.1 Shortcuts-for-Jupyter.pdf
634.0 kB
5. Preprocessing/1.2 data_preprocessing_homework.pptx
310.9 kB
5. Preprocessing/1.3 Absenteeism_data.csv
32.8 kB
6. Machine Learning/1.1 Absenteeism_preprocessed.csv
29.8 kB
5. Preprocessing/1.1 df_preprocessed.csv
29.8 kB
7. Installing MySQL and Getting Acquainted with the Interface/1. Installing MySQL.srt
11.7 kB
2. What is software integration/5. Further Details on APIs.srt
10.6 kB
9. Analyzing the Obtained data in Tableau/2. Analysis in Tableau Age vs Probability.srt
10.3 kB
5. Preprocessing/11. Splitting a Column into Multiple Dummies.srt
10.2 kB
5. Preprocessing/16. Grouping - Transforming Dummy Variables into Categorical Variables.srt
10.2 kB
9. Analyzing the Obtained data in Tableau/4. Analysis in Tableau Reasons vs Probability.srt
9.7 kB
3. Setting up the working environment/4. Installing Anaconda.srt
9.1 kB
2. What is software integration/3. Properties and Definitions Data Connectivity, APIs, and Endpoints.srt
8.8 kB
5. Preprocessing/26. Exploring the Initial Date Column.srt
8.7 kB
6. Machine Learning/2. Creating the Targets for the Logistic Regression.srt
8.6 kB
6. Machine Learning/5. Train-test Split of the Data.srt
8.5 kB
8. Connecting Python and SQL/4. Creating a Database in MySQL.srt
8.2 kB
5. Preprocessing/27. Using the Date Column to Extract the Appropriate Month Value.srt
8.0 kB
6. Machine Learning/8. Interpreting the Logistic Regression Coefficients.srt
8.0 kB
5. Preprocessing/7. Removing Irrelevant Data.srt
8.0 kB
8. Connecting Python and SQL/10. Transferring Data from Jupyter to Workbench - Part I.srt
8.0 kB
3. Setting up the working environment/6. The Jupyter Dashboard - Part 2.srt
7.8 kB
8. Connecting Python and SQL/3. Implementing the 'absenteeism_module' - Part II.srt
7.6 kB
8. Connecting Python and SQL/11. Transferring Data from Jupyter to Workbench - Part II.srt
7.5 kB
6. Machine Learning/10. Interpreting the Important Predictors.srt
7.4 kB
6. Machine Learning/6. Training the Model and Assessing its Accuracy.srt
7.3 kB
9. Analyzing the Obtained data in Tableau/6. Analysis in Tableau Transportation Expense vs Probability.srt
7.2 kB
5. Preprocessing/3. Data at a Glance.srt
7.2 kB
2. What is software integration/9. Definitions and Applications.srt
6.9 kB
6. Machine Learning/12. Testing the Machine Learning Model.srt
6.7 kB
3. Setting up the working environment/2. Why Python and why Jupyter.srt
6.6 kB
6. Machine Learning/7. Extracting the Intercept and Coefficients from a Logistic Regression.srt
6.5 kB
8. Connecting Python and SQL/8. Creating the 'predicted_outputs' table in MySQL.srt
6.0 kB
2. What is software integration/1. Properties and Definitions Data, Servers, Clients, Requests and Responses.srt
6.0 kB
5. Preprocessing/10. Examining the Reasons for Absence.srt
6.0 kB
5. Preprocessing/31. Further Analysis of the DaraFrame Education, Children, Pets.srt
5.8 kB
6. Machine Learning/16. Creating a Module for Later Use of the Model.srt
5.8 kB
6. Machine Learning/13. How to Save the Machine Learning Model and Prepare it for Future Deployment.srt
5.6 kB
2. What is software integration/7. Text Files as Means of Communication.srt
5.6 kB
1. Introduction/1. What Does the Course Cover.srt
5.6 kB
4. What's next in the course/1. Up Ahead.srt
5.5 kB
6. Machine Learning/11. Simplifying the Model (Backward Elimination).srt
5.3 kB
6. Machine Learning/9. Omitting the dummy variables from the Standardization.srt
5.1 kB
5. Preprocessing/17. Concatenating Columns in Python.srt
5.1 kB
8. Connecting Python and SQL/2. Implementing the 'absenteeism_module' - Part I.srt
4.8 kB
6. Machine Learning/1. Exploring the Problem from a Machine Learning Point of View.srt
4.7 kB
5. Preprocessing/28. Introducing Day of the Week.srt
4.4 kB
6. Machine Learning/4. A Bit of Statistical Preprocessing.srt
4.2 kB
5. Preprocessing/4. A Note on Our Usage of Terms with Multiple Meanings.srt
4.2 kB
4. What's next in the course/3. Real-Life Example The Dataset.srt
4.2 kB
5. Preprocessing/2. Data Sets in Python.srt
4.0 kB
4. What's next in the course/2. Real-Life Example Absenteeism at Work.srt
3.9 kB
3. Setting up the working environment/5. The Jupyter Dashboard - Part 1.srt
3.8 kB
5. Preprocessing/23. Implementing Checkpoints in Coding.srt
3.8 kB
8. Connecting Python and SQL/9. Running an SQL SELECT Statement from Python.srt
3.7 kB
6. Machine Learning/3. Selecting the Inputs.srt
3.6 kB
8. Connecting Python and SQL/6. Creating a Connection and Cursor.srt
3.6 kB
8. Connecting Python and SQL/5. Importing and Installing 'pymysql'.srt
3.4 kB
8. Connecting Python and SQL/12. Transferring Data from Jupyter to Workbench - Part III.srt
3.4 kB
7. Installing MySQL and Getting Acquainted with the Interface/3. Setting Up a Connection.srt
3.3 kB
5. Preprocessing/5. ARTICLE - A Brief Overview of Regression Analysis.html
2.9 kB
5. Preprocessing/6. Picking the Appropriate Approach for the Task at Hand.srt
2.9 kB
5. Preprocessing/1. What to Expect from the Next Couple of Sections.html
2.9 kB
7. Installing MySQL and Getting Acquainted with the Interface/2. Installing MySQL on macOS and Unix systems.html
2.7 kB
5. Preprocessing/32. A Final Note on Preprocessing.srt
2.6 kB
5. Preprocessing/14. ARTICLE - Dummy Variables Reasoning.html
2.4 kB
6. Machine Learning/14. ARTICLE - More about 'pickling'.html
2.2 kB
5. Preprocessing/20. Changing Column Order in Pandas DataFrame.srt
1.9 kB
10. Bonus lecture/1. Bonus Lecture Next Steps.html
1.9 kB
3. Setting up the working environment/9. Installing sklearn.srt
1.8 kB
5. Preprocessing/15. Dummy Variables and Their Statistical Importance.srt
1.7 kB
3. Setting up the working environment/1. Setting Up the Environment - An Introduction (Do Not Skip, Please)!.srt
1.3 kB
4. What's next in the course/5. Important Notice Regarding Datasets.html
1.3 kB
5. Preprocessing/29. EXERCISE - Removing Columns.html
1.2 kB
5. Preprocessing/33. A Note on Exporting Your Data as a .csv File.html
883 Bytes
5. Preprocessing/8. EXERCISE - Removing Irrelevant Data.html
873 Bytes
9. Analyzing the Obtained data in Tableau/5. EXERCISE - Transportation Expense vs Probability.html
553 Bytes
3. Setting up the working environment/11. Installing Packages - Solution.html
546 Bytes
5. Preprocessing/22. SOLUTION - Changing Column Order in Pandas DataFrame.html
471 Bytes
9. Analyzing the Obtained data in Tableau/3. EXERCISE - Reasons vs Probability.html
390 Bytes
9. Analyzing the Obtained data in Tableau/1. EXERCISE - Age vs Probability.html
385 Bytes
8. Connecting Python and SQL/1. Are you sure you're all set.html
336 Bytes
8. Connecting Python and SQL/7. EXERCISE - Create 'df_new_obs'.html
322 Bytes
3. Setting up the working environment/7. Jupyter Shortcuts.html
316 Bytes
3. Setting up the working environment/10. Installing Packages - Exercise.html
291 Bytes
6. Machine Learning/15. EXERCISE - Saving the Model (and Scaler).html
284 Bytes
6. Machine Learning/11.1 Logistic Regression prior to Backward Elimination.html
226 Bytes
6. Machine Learning/9.1 Logistic Regression prior to Custom Scaler.html
219 Bytes
6. Machine Learning/15.1 Logistic Regression with Comments.html
210 Bytes
6. Machine Learning/15.2 Logistic Regression.html
196 Bytes
5. Preprocessing/29.2 Preprocessing - df_reason_date_mod.html
191 Bytes
5. Preprocessing/18. EXERCISE - Concatenating Columns in Python.html
189 Bytes
5. Preprocessing/29.1 Removing Columns.html
188 Bytes
5. Preprocessing/23.1 Implementing Checkpoints in Coding.html
176 Bytes
5. Preprocessing/32.1 Exercises and Solutions.html
170 Bytes
5. Preprocessing/21. EXERCISE - Changing Column Order in Pandas DataFrame.html
167 Bytes
5. Preprocessing/32.2 Preprocessing - Lectures.html
167 Bytes
2. What is software integration/10. Definitions and Applications.html
164 Bytes
2. What is software integration/2. Properties and Definitions Data, Servers, Clients, Requests and Responses.html
164 Bytes
2. What is software integration/4. Properties and Definitions Data Connectivity, APIs, and Endpoints.html
164 Bytes
2. What is software integration/6. Further Details on APIs.html
164 Bytes
2. What is software integration/8. Text Files as Means of Communication.html
164 Bytes
3. Setting up the working environment/3. Why Python and why Jupyter.html
164 Bytes
3. Setting up the working environment/8. The Jupyter Dashboard.html
164 Bytes
4. What's next in the course/4. Real-Life Example The Dataset.html
164 Bytes
5. Preprocessing/32.3 Preprocessing - df_preprocessed.html
156 Bytes
8. Connecting Python and SQL/12.1 Integration.html
154 Bytes
5. Preprocessing/19. SOLUTION - Concatenating Columns in Python.html
142 Bytes
5. Preprocessing/24. EXERCISE - Implementing Checkpoints in Coding.html
137 Bytes
1. Introduction/1.1 Course Resources - Complete Package.html
134 Bytes
8. Connecting Python and SQL/1.1 5 Files Needed to Deploy the Model.html
134 Bytes
5. Preprocessing/12. EXERCISE - Splitting a Column into Multiple Dummies.html
130 Bytes
[Tutorialsplanet.NET].url
128 Bytes
5. Preprocessing/25. SOLUTION - Implementing Checkpoint in Coding.html
117 Bytes
5. Preprocessing/13. SOLUTION - Splitting a Column into Multiple Dummies.html
116 Bytes
5. Preprocessing/9. SOLUTION - Removing Irrelevant Data.html
113 Bytes
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