| File | Size |
|---|
| !! IMPORTANT Note !!.txt | 298.00 B |
| !!! Please Support !!! [CoursesGhar.Com].txt | 197.00 B |
| 00. Websites You May Like/A1movies.com.pk.url | 116.00 B |
| 00. Websites You May Like/CoursesGhar.com.url | 114.00 B |
| 1. Software Integration/1. Introduction to Data, Servers, Clients, Requests, and Responses.mp4 | 30.27 MB |
| 1. Software Integration/2. Introduction to Data Connectivity, APIs, and Endpoints.mp4 | 56.20 MB |
| 1. Software Integration/3. More on APIs.mp4 | 55.78 MB |
| 1. Software Integration/4. Exchanging Information using Text Files.mp4 | 29.46 MB |
| 1. Software Integration/5. Software Integration - Python-SQL-Tableau.mp4 | 35.37 MB |
| 2. What_s Next in the Course_/1. What_s next in the course.mp4 | 25.84 MB |
| 2. What_s Next in the Course_/2. Defining the Task - Absenteeism at Work.mp4 | 25.54 MB |
| 2. What_s Next in the Course_/3. The Data Set.mp4 | 25.81 MB |
| 3. Preprocessing the _Absenteeism_data_/1. Importing the Data Set in Python.mp4 | 13.03 MB |
| 3. Preprocessing the _Absenteeism_data_/10. Concatenating Column Values.mp4 | 18.38 MB |
| 3. Preprocessing the _Absenteeism_data_/11. Reordering Columns.mp4 | 6.94 MB |
| 3. Preprocessing the _Absenteeism_data_/12. Creating Checkpoints in Jupyter.mp4 | 13.01 MB |
| 3. Preprocessing the _Absenteeism_data_/13. Working on the _Date_ Column.mp4 | 26.59 MB |
| 3. Preprocessing the _Absenteeism_data_/14. Extracting the Month Value.mp4 | 24.11 MB |
| 3. Preprocessing the _Absenteeism_data_/15. Creating the _Day of the Week_ Column.mp4 | 15.08 MB |
| 3. Preprocessing the _Absenteeism_data_/16. Analyzing the Next 5 Columns in our DataFrame.mp4 | 14.11 MB |
| 3. Preprocessing the _Absenteeism_data_/17. Modifying _Education_ and discussing _Children_ and _Pets_.mp4 | 18.79 MB |
| 3. Preprocessing the _Absenteeism_data_/18. Final Remarks on the Data Preprocessing Part of the Exercise.mp4 | 22.05 MB |
| 3. Preprocessing the _Absenteeism_data_/2. Eyeballing the Data.mp4 | 39.36 MB |
| 3. Preprocessing the _Absenteeism_data_/3. Introduction to Terms with Multiple Meanings.mp4 | 20.06 MB |
| 3. Preprocessing the _Absenteeism_data_/4. An Analytical Approach to Solving the Task.mp4 | 10.93 MB |
| 3. Preprocessing the _Absenteeism_data_/5. Dropping the _ID_ Column.mp4 | 34.34 MB |
| 3. Preprocessing the _Absenteeism_data_/6. Analysis of the _Reason for Absence_ Column.mp4 | 20.25 MB |
| 3. Preprocessing the _Absenteeism_data_/7. Converting a Feature into Multiple Dummy Variables.mp4 | 46.70 MB |
| 3. Preprocessing the _Absenteeism_data_/8. Working with Dummy Variables from a Statistical Perspective.mp4 | 5.75 MB |
| 3. Preprocessing the _Absenteeism_data_/9. Grouping the Various Reasons for Absence.mp4 | 38.49 MB |
| 4. Applying Machine Learning to the Preprocessed Data/1. Exploring the Problem from a Machine Learning Point of View.mp4 | 25.50 MB |
| 4. Applying Machine Learning to the Preprocessed Data/10. Interpreting the (Important) Coefficients.mp4 | 28.11 MB |
| 4. Applying Machine Learning to the Preprocessed Data/11. Simplifying the Model (Backward Elimination).mp4 | 37.87 MB |
| 4. Applying Machine Learning to the Preprocessed Data/12. Testing the Logistic Regression Model.mp4 | 41.45 MB |
| 4. Applying Machine Learning to the Preprocessed Data/13. Saving the Logistic Regression Model.mp4 | 30.40 MB |
| 4. Applying Machine Learning to the Preprocessed Data/14. Creating a module for later use of the model.mp4 | 49.61 MB |
| 4. Applying Machine Learning to the Preprocessed Data/2. Creating the Targets for the Regression.mp4 | 34.39 MB |
| 4. Applying Machine Learning to the Preprocessed Data/3. Selecting the Inputs for the Regression.mp4 | 12.26 MB |
| 4. Applying Machine Learning to the Preprocessed Data/4. Standardizing the Dataset for Better Results.mp4 | 15.62 MB |
| 4. Applying Machine Learning to the Preprocessed Data/5. Train-Test Split.mp4 | 39.92 MB |
| 4. Applying Machine Learning to the Preprocessed Data/6. Training and evaluating the model.mp4 | 32.65 MB |
| 4. Applying Machine Learning to the Preprocessed Data/7. Extracting the Intercept and Coefficients.mp4 | 33.39 MB |
| 4. Applying Machine Learning to the Preprocessed Data/8. Interpreting the Coefficients.mp4 | 46.47 MB |
| 4. Applying Machine Learning to the Preprocessed Data/9. Creating a Custom Scaler to Standardize Only Numerical Features.mp4 | 33.87 MB |
| 5. Connecting Python and SQL/1. Loading the _absenteeism_module_.mp4 | 15.57 MB |
| 5. Connecting Python and SQL/10. Moving Data from Python to SQL - Part III.mp4 | 22.42 MB |
| 5. Connecting Python and SQL/2. Working with the _absenteeism_module_.mp4 | 28.36 MB |
| 5. Connecting Python and SQL/3. Creating a Database Structure in MySQL.mp4 | 30.34 MB |
| 5. Connecting Python and SQL/4. Installing and Importing _pymysql_.mp4 | 11.17 MB |
| 5. Connecting Python and SQL/5. Setting up a Connection and Creating a Cursor.mp4 | 10.44 MB |
| 5. Connecting Python and SQL/6. Creating the _predicted_outputs_ table in MySQL.mp4 | 27.40 MB |
| 5. Connecting Python and SQL/7. Executing an SQL Query from Python.mp4 | 12.54 MB |
| 5. Connecting Python and SQL/8. Moving Data from Python to SQL - Part I.mp4 | 45.36 MB |
| 5. Connecting Python and SQL/9. Moving Data from Python to SQL - Part II.mp4 | 32.11 MB |
| 6. Analyzing the Obtained Data in Tableau/1. Tableau Analysis - Age vs Probability.mp4 | 26.42 MB |
| 6. Analyzing the Obtained Data in Tableau/2. Tableau Analysis - Reasons vs Probability.mp4 | 30.18 MB |
| 6. Analyzing the Obtained Data in Tableau/3. Tableau Analysis - Transportation Expense vs Probability.mp4 | 17.35 MB |
| Join Our Telegram Group For More Updates !!!.url | 138.00 B |
| Uploaded by [Coursesghar.com].txt | 1.10 kB |
| Visit coursesghar.com for more awesome tutorials.url | 114.00 B |
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