Udemy - ML for Business Managers: Build Regression model in R Studio [FCS]

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1. Introduction
  • 1. Welcome to the course!.mp4 (15.4 MB)
  • 1. Welcome to the course!.srt (3.4 KB)
  • 2. Course Resources.html (0.3 KB)
  • 3. Course contents.mp4 (47.0 MB)
  • 3. Course contents.srt (10.2 KB)
  • 3.1 00_Introduction_01.pdf (791.5 KB)
  • 4. This is a milestone!.mp4 (20.7 MB)
  • 4. This is a milestone!.srt (3.8 KB)
2. Basics of Statistics
  • 1. Types of Data.mp4 (21.8 MB)
  • 1. Types of Data.srt (5.0 KB)
  • 1.1 01_01_Lecture_TypesOfData.pdf (177.7 KB)
  • 2. Types of Statistics.mp4 (10.9 MB)
  • 2. Types of Statistics.srt (3.2 KB)
  • 2.1 01_02_Lecture_TypesOfStatistics.pdf (171.7 KB)
  • 3. Describing the data graphically.mp4 (65.4 MB)
  • 3. Describing the data graphically.srt (12.8 KB)
  • 3.1 01_03_Lecture_DataSummaryandGraph.pdf (317.9 KB)
  • 4. Measures of Centers.mp4 (38.6 MB)
  • 4. Measures of Centers.srt (7.9 KB)
  • 4.1 01_04_Lecture_Centers.pdf (313.0 KB)
  • 5. Practice Exercise 1.html (0.3 KB)
  • 5.1 Exercise 1.pdf (553.8 KB)
  • 6. Measures of Dispersion.mp4 (22.9 MB)
  • 6. Measures of Dispersion.srt (5.2 KB)
  • 7. Practice Exercise 2.html (0.3 KB)
  • 7.1 Exercise 2.pdf (479.9 KB)
3. Getting started with R and R studio
  • 1. Installing R and R studio.mp4 (40.8 MB)
  • 1. Installing R and R studio.srt (7.3 KB)
  • 2. Basics of R and R studio.mp4 (48.2 MB)
  • 2. Basics of R and R studio.srt (14.3 KB)
  • 3. Packages in R.mp4 (98.7 MB)
  • 3. Packages in R.srt (14.4 KB)
  • 4. Inputting data part 1 Inbuilt datasets of R.mp4 (46.2 MB)
  • 4. Inputting data part 1 Inbuilt datasets of R.srt (5.5 KB)
  • 5. Inputting data part 2 Manual data entry.mp4 (30.9 MB)
  • 5. Inputting data part 2 Manual data entry.srt (3.6 KB)
  • 6. Inputting data part 3 Importing from CSV or Text files.mp4 (69.1 MB)
  • 6. Inputting data part 3 Importing from CSV or Text files.srt (8.3 KB)
  • 6.1 Customer.csv (74.0 KB)
  • 7. Creating Barplots in R.mp4 (117.6 MB)
  • 7. Creating Barplots in R.srt (18.2 KB)
  • 8. Creating Histograms in R.mp4 (51.5 MB)
  • 8. Creating Histograms in R.srt (7.5 KB)
4. Introduction to Machine Learning
  • 1. Introduction to Machine Learning.mp4 (123.9 MB)
  • 1. Introduction to Machine Learning.srt (23.2 KB)
  • 1.1 Lecture_machineLearning.pdf (991.6 KB)
  • 2. Building a Machine Learning model.mp4 (45.3 MB)
  • 2. Building a Machine Learning model.srt (12.8 KB)
  • 2.1 Lecture_machineLearning.pdf (1,001.6 KB)
  • 3. Introduction to Machine learning quiz.html (0.2 KB)
5. Data Preprocessing
  • 1. Gathering Business Knowledge.mp4 (25.1 MB)
  • 1. Gathering Business Knowledge.srt (3.9 KB)
  • 1.1 03_01_PDE_Business_knowledge.pdf (163.9 KB)
  • 10. Outlier Treatment in R.mp4 (38.0 MB)
  • 10. Outlier Treatment in R.srt (4.3 KB)
  • 11. Project Exercise 3.html (0.2 KB)
  • 12. Missing Value imputation.mp4 (27.6 MB)
  • 12. Missing Value imputation.srt (4.1 KB)
  • 12.1 04_05_PDE_Missing_value.pdf (315.7 KB)
  • 13. Missing Value imputation in R.mp4 (31.8 MB)
  • 13. Missing Value imputation in R.srt (3.5 KB)
  • 14. Project Exercise 4.html (0.2 KB)
  • 15. Seasonality in Data.mp4 (20.9 MB)
  • 15. Seasonality in Data.srt (3.8 KB)
  • 15.1 04_07_PDE_Seasonality.pdf (364.1 KB)
  • 16. Bi-variate Analysis and Variable Transformation.mp4 (113.8 MB)
  • 16. Bi-variate Analysis and Variable Transformation.srt (18.3 KB)
  • 16.1 04_07_Variable_Transformation.pdf (422.8 KB)
  • 17. Variable transformation in R.mp4 (67.9 MB)
  • 17. Variable transformation in R.srt (9.1 KB)
  • 18. Project Exercise 5.html (0.3 KB)
  • 19. Non Usable Variables.mp4 (24.0 MB)
  • 19. Non Usable Variables.srt (5.4 KB)
  • 19.1 04_08_PDE_Non_Usable_var.pdf (148.3 KB)
  • 2. Data Exploration.mp4 (23.4 MB)
  • 2. Data Exploration.srt (3.6 KB)
  • 2.1 03_02_PDE_Data_exploration.pdf (322.9 KB)
  • 20. Dummy variable creation Handling qualitative data.mp4 (40.6 MB)
  • 20. Dummy variable creation Handling qualitative data.srt (4.9 KB)
  • 20.1 04_11_Dummy_Var.pdf (163.0 KB)
  • 21. Dummy variable creation in R.mp4 (52.3 MB)
  • 21. Dummy variable creation in R.srt (5.2 KB)
  • 22. Project Exercise 6.html (0.2 KB)
  • 23. Correlation Matrix and cause-effect relationship.mp4 (81.3 MB)
  • 23. Correlation Matrix and cause-effect relationship.srt (11.0 KB)
  • 23.1 04_10_Correlation.pdf (256.9 KB)
  • 24. Correlation Matrix in R.mp4 (95.1 MB)
  • 24. Correlation Matrix in R.srt (9.1 KB)
  • 25. Project Exercise 7.html (0.3 KB)
  • 26. Quiz.html (0.2 KB)
  • 3. The Data and the Data Dictionary.mp4 (78.6 MB)
  • 3. The Data and the Data Dictionary.srt (7.8 KB)
  • 3.1 03_03_PDE_Raw_Data_Analysis_Uni.pdf (332.0 KB)
  • 3.2 House_Price.csv (63.5 KB)
  • 4. Importing the dataset into R.mp4 (16.0 MB)
  • 4. Importing the dataset into R.srt (2.6 KB)
  • 4.1 House_Price.csv (53.5 KB)
  • 4.2 R_Linear.zip (1.1 KB)
  • 5. Project Exercise 1.html (0.4 KB)
  • 5.1 Movie_collection_train.csv (43.3 KB)
  • 6. Univariate Analysis and EDD.mp4 (27.3 MB)
  • 6. Univariate Analysis and EDD.srt (3.4 KB)
  • 6.1 03_04_PDE_Univariate_Analysis_Uni.pdf (333.4 KB)
  • 7. EDD in R.mp4 (112.3 MB)
  • 7. EDD in R.srt (11.6 KB)
  • 8. Project Exercise 2.html (0.2 KB)
  • 9. Outlier Treatment.mp4 (27.8 MB)

Description

Udemy - ML for Business Managers: Build Regression model in R Studio [FCS]

Simple Regression & Multiple Regression| must-know for Machine Learning & Econometrics | Linear Regression in R studio

Created by Start-Tech Academy
Last updated 11/2021
English
English [Auto]

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Udemy - ML for Business Managers: Build Regression model in R Studio [FCS]

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Download torrent
2.8 GB
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Udemy - ML for Business Managers: Build Regression model in R Studio [FCS]

Torrent hash: E4958120FB7BCF38A84D5B6B9A555FEF33F2BEE8