365 Data Science SQL Tableau Python CoursesGhar | 482C76A5556DFD7FC1A84D08F703BF18D74184D4

365 Data Science SQL Tableau Python CoursesGhar

Name	365 Data Science - SQL + Tableau + Python [CoursesGhar]	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.5 GB
Total Files	60
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Hash	482C76A5556DFD7FC1A84D08F703BF18D74184D4

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1. Software Integration/
1. Introduction to Data, Servers, Clients, Requests, and Responses.mp4	31.7 MB
2. Introduction to Data Connectivity, APIs, and Endpoints.mp4	58.9 MB
3. More on APIs.mp4	58.5 MB
4. Exchanging Information using Text Files.mp4	30.9 MB
5. Software Integration - Python-SQL-Tableau.mp4	37.1 MB
2. What_s Next in the Course_/
1. What_s next in the course.mp4	27.1 MB
2. Defining the Task - Absenteeism at Work.mp4	26.8 MB
3. The Data Set.mp4	27.1 MB
3. Preprocessing the _Absenteeism_data_/
1. Importing the Data Set in Python.mp4	13.7 MB
10. Concatenating Column Values.mp4	19.3 MB
11. Reordering Columns.mp4	7.3 MB
12. Creating Checkpoints in Jupyter.mp4	13.6 MB
13. Working on the _Date_ Column.mp4	27.9 MB
14. Extracting the Month Value.mp4	25.3 MB
15. Creating the _Day of the Week_ Column.mp4	15.8 MB
16. Analyzing the Next 5 Columns in our DataFrame.mp4	14.8 MB
17. Modifying _Education_ and discussing _Children_ and _Pets_.mp4	19.7 MB
18. Final Remarks on the Data Preprocessing Part of the Exercise.mp4	23.1 MB
2. Eyeballing the Data.mp4	41.3 MB
3. Introduction to Terms with Multiple Meanings.mp4	21.0 MB
4. An Analytical Approach to Solving the Task.mp4	11.5 MB
5. Dropping the _ID_ Column.mp4	36.0 MB
6. Analysis of the _Reason for Absence_ Column.mp4	21.2 MB
7. Converting a Feature into Multiple Dummy Variables.mp4	49.0 MB
8. Working with Dummy Variables from a Statistical Perspective.mp4	6.0 MB
9. Grouping the Various Reasons for Absence.mp4	40.4 MB
4. Applying Machine Learning to the Preprocessed Data/
1. Exploring the Problem from a Machine Learning Point of View.mp4	26.7 MB
10. Interpreting the (Important) Coefficients.mp4	29.5 MB
11. Simplifying the Model (Backward Elimination).mp4	39.7 MB
12. Testing the Logistic Regression Model.mp4	43.5 MB
13. Saving the Logistic Regression Model.mp4	31.9 MB
14. Creating a module for later use of the model.mp4	52.0 MB
2. Creating the Targets for the Regression.mp4	36.1 MB
3. Selecting the Inputs for the Regression.mp4	12.9 MB
4. Standardizing the Dataset for Better Results.mp4	16.4 MB
5. Train-Test Split.mp4	41.9 MB
6. Training and evaluating the model.mp4	34.2 MB
7. Extracting the Intercept and Coefficients.mp4	35.0 MB
8. Interpreting the Coefficients.mp4	48.7 MB
9. Creating a Custom Scaler to Standardize Only Numerical Features.mp4	35.5 MB
5. Connecting Python and SQL/
1. Loading the _absenteeism_module_.mp4	16.3 MB
10. Moving Data from Python to SQL - Part III.mp4	23.5 MB
2. Working with the _absenteeism_module_.mp4	29.7 MB
3. Creating a Database Structure in MySQL.mp4	31.8 MB
4. Installing and Importing _pymysql_.mp4	11.7 MB
5. Setting up a Connection and Creating a Cursor.mp4	10.9 MB
6. Creating the _predicted_outputs_ table in MySQL.mp4	28.7 MB
7. Executing an SQL Query from Python.mp4	13.1 MB
8. Moving Data from Python to SQL - Part I.mp4	47.6 MB
9. Moving Data from Python to SQL - Part II.mp4	33.7 MB
6. Analyzing the Obtained Data in Tableau/
1. Tableau Analysis - Age vs Probability.mp4	27.7 MB
2. Tableau Analysis - Reasons vs Probability.mp4	31.6 MB
3. Tableau Analysis - Transportation Expense vs Probability.mp4	18.2 MB
Total files 60