Tutorialsplanet NET Udemy - Python SQL Tableau Integrating Python SQL and Tableau

1. 1. Introduction/1. What Does the Course Cover.mp456.19MB
2. 2. What is software integration/1. Properties and Definitions Data, Servers, Clients, Requests and Responses.mp469.16MB
3. 2. What is software integration/3. Properties and Definitions Data Connectivity, APIs, and Endpoints.mp4104.22MB
4. 2. What is software integration/5. Further Details on APIs.mp4115.66MB
5. 2. What is software integration/7. Text Files as Means of Communication.mp460.42MB
6. 2. What is software integration/9. Definitions and Applications.mp463.7MB
7. 3. Setting up the working environment/1. Setting Up the Environment - An Introduction (Do Not Skip, Please)!.mp45.34MB
8. 3. Setting up the working environment/2. Why Python and why Jupyter.mp441.07MB
9. 3. Setting up the working environment/4. Installing Anaconda.mp451.01MB
10. 3. Setting up the working environment/5. The Jupyter Dashboard - Part 1.mp413.47MB
11. 3. Setting up the working environment/6. The Jupyter Dashboard - Part 2.mp428.65MB
12. 3. Setting up the working environment/9. Installing sklearn.mp47.77MB
13. 4. What's next in the course/1. Up Ahead.mp452.32MB
14. 4. What's next in the course/2. Real-Life Example Absenteeism at Work.mp439.17MB
15. 4. What's next in the course/3. Real-Life Example The Dataset.mp440.91MB
16. 5. Preprocessing/10. Examining the Reasons for Absence.mp440.6MB
17. 5. Preprocessing/11. Splitting a Column into Multiple Dummies.mp481.03MB
18. 5. Preprocessing/15. Dummy Variables and Their Statistical Importance.mp413.8MB
19. 5. Preprocessing/16. Grouping - Transforming Dummy Variables into Categorical Variables.mp474.6MB
20. 5. Preprocessing/17. Concatenating Columns in Python.mp438.76MB
21. 5. Preprocessing/2. Data Sets in Python.mp423.15MB
22. 5. Preprocessing/20. Changing Column Order in Pandas DataFrame.mp414.05MB
23. 5. Preprocessing/23. Implementing Checkpoints in Coding.mp425.7MB
24. 5. Preprocessing/26. Exploring the Initial Date Column.mp457.3MB
25. 5. Preprocessing/27. Using the Date Column to Extract the Appropriate Month Value.mp447.76MB
26. 5. Preprocessing/28. Introducing Day of the Week.mp428MB
27. 5. Preprocessing/3. Data at a Glance.mp461.83MB
28. 5. Preprocessing/30. Further Analysis of the DataFrame Next 5 Columns.mp429.53MB
29. 5. Preprocessing/31. Further Analysis of the DaraFrame Education, Children, Pets.mp439.54MB
30. 5. Preprocessing/32. A Final Note on Preprocessing.mp421.62MB
31. 5. Preprocessing/4. A Note on Our Usage of Terms with Multiple Meanings.mp427.9MB
32. 5. Preprocessing/6. Picking the Appropriate Approach for the Task at Hand.mp420.22MB
33. 5. Preprocessing/7. Removing Irrelevant Data.mp461.73MB
34. 6. Machine Learning/1. Exploring the Problem from a Machine Learning Point of View.mp427.51MB
35. 6. Machine Learning/10. Interpreting the Important Predictors.mp440.45MB
36. 6. Machine Learning/11. Simplifying the Model (Backward Elimination).mp439.59MB
37. 6. Machine Learning/12. Testing the Machine Learning Model.mp449.13MB
38. 6. Machine Learning/13. How to Save the Machine Learning Model and Prepare it for Future Deployment.mp437.45MB
39. 6. Machine Learning/16. Creating a Module for Later Use of the Model.mp444.58MB
40. 6. Machine Learning/2. Creating the Targets for the Logistic Regression.mp445.83MB
41. 6. Machine Learning/3. Selecting the Inputs.mp416.76MB
42. 6. Machine Learning/4. A Bit of Statistical Preprocessing.mp420.6MB
43. 6. Machine Learning/5. Train-test Split of the Data.mp452.7MB
44. 6. Machine Learning/6. Training the Model and Assessing its Accuracy.mp441.64MB
45. 6. Machine Learning/7. Extracting the Intercept and Coefficients from a Logistic Regression.mp438.82MB
46. 6. Machine Learning/8. Interpreting the Logistic Regression Coefficients.mp452.36MB
47. 6. Machine Learning/9. Omitting the dummy variables from the Standardization.mp441.19MB
48. 7. Installing MySQL and Getting Acquainted with the Interface/1. Installing MySQL.mp480.95MB
49. 7. Installing MySQL and Getting Acquainted with the Interface/3. Setting Up a Connection.mp417.57MB
50. 7. Installing MySQL and Getting Acquainted with the Interface/4. Introduction to the MySQL Interface.mp437.22MB
51. 8. Connecting Python and SQL/10. Transferring Data from Jupyter to Workbench - Part I.mp476.24MB
52. 8. Connecting Python and SQL/11. Transferring Data from Jupyter to Workbench - Part II.mp458.22MB
53. 8. Connecting Python and SQL/12. Transferring Data from Jupyter to Workbench - Part III.mp432.8MB
54. 8. Connecting Python and SQL/2. Implementing the 'absenteeism_module' - Part I.mp425.45MB
55. 8. Connecting Python and SQL/3. Implementing the 'absenteeism_module' - Part II.mp454.29MB
56. 8. Connecting Python and SQL/4. Creating a Database in MySQL.mp458.95MB
57. 8. Connecting Python and SQL/5. Importing and Installing 'pymysql'.mp419.03MB
58. 8. Connecting Python and SQL/6. Creating a Connection and Cursor.mp420.97MB
59. 8. Connecting Python and SQL/8. Creating the 'predicted_outputs' table in MySQL.mp452.45MB
60. 8. Connecting Python and SQL/9. Running an SQL SELECT Statement from Python.mp425.43MB
61. 9. Analyzing the Obtained data in Tableau/2. Analysis in Tableau Age vs Probability.mp456.48MB
62. 9. Analyzing the Obtained data in Tableau/4. Analysis in Tableau Reasons vs Probability.mp459.32MB
63. 9. Analyzing the Obtained data in Tableau/6. Analysis in Tableau Transportation Expense vs Probability.mp440.63MB