365 Data Science - SQL + Tableau + Python [CoursesGhar] - 磁力管家

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种子哈希：482c76a5556dfd7fc1a84d08f703bf18d74184d4
文档大小：1.5 GB
文档个数：60个文档
下载次数：334次
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收录时间：2022-01-14
最近下载：2025-05-08
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365 Data Science - SQL + Tableau + Python [CoursesGhar]的二维码

文档列表

1. Software Integration/2. Introduction to Data Connectivity, APIs, and Endpoints.mp4 58.9 MB
1. Software Integration/3. More on APIs.mp4 58.5 MB
4. Applying Machine Learning to the Preprocessed Data/14. Creating a module for later use of the model.mp4 52.0 MB
3. Preprocessing the _Absenteeism_data_/7. Converting a Feature into Multiple Dummy Variables.mp4 49.0 MB
4. Applying Machine Learning to the Preprocessed Data/8. Interpreting the Coefficients.mp4 48.7 MB
5. Connecting Python and SQL/8. Moving Data from Python to SQL - Part I.mp4 47.6 MB
4. Applying Machine Learning to the Preprocessed Data/12. Testing the Logistic Regression Model.mp4 43.5 MB
4. Applying Machine Learning to the Preprocessed Data/5. Train-Test Split.mp4 41.9 MB
3. Preprocessing the _Absenteeism_data_/2. Eyeballing the Data.mp4 41.3 MB
3. Preprocessing the _Absenteeism_data_/9. Grouping the Various Reasons for Absence.mp4 40.4 MB
4. Applying Machine Learning to the Preprocessed Data/11. Simplifying the Model (Backward Elimination).mp4 39.7 MB
1. Software Integration/5. Software Integration - Python-SQL-Tableau.mp4 37.1 MB
4. Applying Machine Learning to the Preprocessed Data/2. Creating the Targets for the Regression.mp4 36.1 MB
3. Preprocessing the _Absenteeism_data_/5. Dropping the _ID_ Column.mp4 36.0 MB
4. Applying Machine Learning to the Preprocessed Data/9. Creating a Custom Scaler to Standardize Only Numerical Features.mp4 35.5 MB
4. Applying Machine Learning to the Preprocessed Data/7. Extracting the Intercept and Coefficients.mp4 35.0 MB
4. Applying Machine Learning to the Preprocessed Data/6. Training and evaluating the model.mp4 34.2 MB
5. Connecting Python and SQL/9. Moving Data from Python to SQL - Part II.mp4 33.7 MB
4. Applying Machine Learning to the Preprocessed Data/13. Saving the Logistic Regression Model.mp4 31.9 MB
5. Connecting Python and SQL/3. Creating a Database Structure in MySQL.mp4 31.8 MB
1. Software Integration/1. Introduction to Data, Servers, Clients, Requests, and Responses.mp4 31.7 MB
6. Analyzing the Obtained Data in Tableau/2. Tableau Analysis - Reasons vs Probability.mp4 31.6 MB
1. Software Integration/4. Exchanging Information using Text Files.mp4 30.9 MB
5. Connecting Python and SQL/2. Working with the _absenteeism_module_.mp4 29.7 MB
4. Applying Machine Learning to the Preprocessed Data/10. Interpreting the (Important) Coefficients.mp4 29.5 MB
5. Connecting Python and SQL/6. Creating the _predicted_outputs_ table in MySQL.mp4 28.7 MB
3. Preprocessing the _Absenteeism_data_/13. Working on the _Date_ Column.mp4 27.9 MB
6. Analyzing the Obtained Data in Tableau/1. Tableau Analysis - Age vs Probability.mp4 27.7 MB
2. What_s Next in the Course_/1. What_s next in the course.mp4 27.1 MB
2. What_s Next in the Course_/3. The Data Set.mp4 27.1 MB
2. What_s Next in the Course_/2. Defining the Task - Absenteeism at Work.mp4 26.8 MB
4. Applying Machine Learning to the Preprocessed Data/1. Exploring the Problem from a Machine Learning Point of View.mp4 26.7 MB
3. Preprocessing the _Absenteeism_data_/14. Extracting the Month Value.mp4 25.3 MB
5. Connecting Python and SQL/10. Moving Data from Python to SQL - Part III.mp4 23.5 MB
3. Preprocessing the _Absenteeism_data_/18. Final Remarks on the Data Preprocessing Part of the Exercise.mp4 23.1 MB
3. Preprocessing the _Absenteeism_data_/6. Analysis of the _Reason for Absence_ Column.mp4 21.2 MB
3. Preprocessing the _Absenteeism_data_/3. Introduction to Terms with Multiple Meanings.mp4 21.0 MB
3. Preprocessing the _Absenteeism_data_/17. Modifying _Education_ and discussing _Children_ and _Pets_.mp4 19.7 MB
3. Preprocessing the _Absenteeism_data_/10. Concatenating Column Values.mp4 19.3 MB
6. Analyzing the Obtained Data in Tableau/3. Tableau Analysis - Transportation Expense vs Probability.mp4 18.2 MB
4. Applying Machine Learning to the Preprocessed Data/4. Standardizing the Dataset for Better Results.mp4 16.4 MB
5. Connecting Python and SQL/1. Loading the _absenteeism_module_.mp4 16.3 MB
3. Preprocessing the _Absenteeism_data_/15. Creating the _Day of the Week_ Column.mp4 15.8 MB
3. Preprocessing the _Absenteeism_data_/16. Analyzing the Next 5 Columns in our DataFrame.mp4 14.8 MB
3. Preprocessing the _Absenteeism_data_/1. Importing the Data Set in Python.mp4 13.7 MB
3. Preprocessing the _Absenteeism_data_/12. Creating Checkpoints in Jupyter.mp4 13.6 MB
5. Connecting Python and SQL/7. Executing an SQL Query from Python.mp4 13.1 MB
4. Applying Machine Learning to the Preprocessed Data/3. Selecting the Inputs for the Regression.mp4 12.9 MB
5. Connecting Python and SQL/4. Installing and Importing _pymysql_.mp4 11.7 MB
3. Preprocessing the _Absenteeism_data_/4. An Analytical Approach to Solving the Task.mp4 11.5 MB
5. Connecting Python and SQL/5. Setting up a Connection and Creating a Cursor.mp4 10.9 MB
3. Preprocessing the _Absenteeism_data_/11. Reordering Columns.mp4 7.3 MB
3. Preprocessing the _Absenteeism_data_/8. Working with Dummy Variables from a Statistical Perspective.mp4 6.0 MB
Uploaded by [Coursesghar.com].txt 1.1 kB
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