Download Udemy - Complete Machine Learning with R Studio - ML for 2023 [FCS] torrent

Udemy - Complete Machine Learning with R Studio - ML for 2023 [FCS]

Torrent:	Udemy - Complete Machine Learning with R Studio - ML for 2023 [FCS]
Description:	TO GET DIRECT DOWNLOAD LINKS OR GOOGLE DRIVE LINKS VISIT OUR WEBSITE FOR MORE PREMIUM UDEMY COURSES VISIT: https://freecoursesite.com Udemy - Complete Machine Learning with R Studio - ML for 2023 [FCS] Linear & Logistic Regression, Decision Trees, XGBoost, SVM & other ML models in R programming language - R studio. Created by Start-Tech Academy Last updated 5/2023 English English [Auto]
Downloads:	59
Category:	Other /Tutorials
Size:	5.5 GB
Show Files »	[FreeCourseSite.com] Udemy - Complete Machine Learning with R Studio - ML for 2023 0. Websites you may like [CourseClub.Me].url (0.1 KB) [FreeCourseSite.com].url (0.1 KB) [GigaCourse.Com].url (0.0 KB) 1. Welcome to the course 1. Introduction.mp4 (21.2 MB) 1. Introduction.srt (2.9 KB) 2. Course Resources.html (0.3 KB) 10. Linear Discriminant Analysis 1. Linear Discriminant Analysis.mp4 (48.4 MB) 1. Linear Discriminant Analysis.srt (12.3 KB) 2. Linear Discriminant Analysis in R.mp4 (89.5 MB) 2. Linear Discriminant Analysis in R.srt (10.5 KB) 11. K-Nearest Neighbors 0. Websites you may like [CourseClub.Me].url (0.1 KB) [FreeCourseSite.com].url (0.1 KB) [GigaCourse.Com].url (0.0 KB) 1. Test-Train Split.mp4 (45.4 MB) 1. Test-Train Split.srt (11.0 KB) 2. Test-Train Split in R.mp4 (90.2 MB) 2. Test-Train Split in R.srt (10.3 KB) 3. K-Nearest Neighbors classifier.mp4 (83.3 MB) 3. K-Nearest Neighbors classifier.srt (10.3 KB) 4. K-Nearest Neighbors in R.mp4 (79.6 MB) 4. K-Nearest Neighbors in R.srt (9.4 KB) 12. Comparing results from 3 models 1. Understanding the results of classification models.mp4 (45.8 MB) 1. Understanding the results of classification models.srt (7.8 KB) 2. Summary of the three models.mp4 (25.1 MB) 2. Summary of the three models.srt (6.2 KB) 13. Simple Decision Trees 1. Introduction to Decision trees.mp4 (44.8 MB) 1. Introduction to Decision trees.srt (4.6 KB) 10. Pruning a Tree in R.mp4 (97.0 MB) 10. Pruning a Tree in R.srt (11.8 KB) 2. Basics of Decision Trees.mp4 (50.6 MB) 2. Basics of Decision Trees.srt (13.2 KB) 3. Understanding a Regression Tree.mp4 (52.2 MB) 3. Understanding a Regression Tree.srt (14.0 KB) 4. The stopping criteria for controlling tree growth.mp4 (16.5 MB) 4. The stopping criteria for controlling tree growth.srt (4.3 KB) 5. Course resources Notes and Datasets.html (0.1 KB) 5.1 Files_Dt_r.zip (2.1 MB) 6. Importing the Data set into R.mp4 (51.8 MB) 6. Importing the Data set into R.srt (8.8 KB) 7. Splitting Data into Test and Train Set in R.mp4 (52.6 MB) 7. Splitting Data into Test and Train Set in R.srt (7.3 KB) 8. Building a Regression Tree in R.mp4 (121.9 MB) 8. Building a Regression Tree in R.srt (18.9 KB) 9. Pruning a tree.mp4 (22.2 MB) 9. Pruning a tree.srt (5.4 KB) 14. Simple Classification Tree 1. Classification Trees.mp4 (33.0 MB) 1. Classification Trees.srt (8.1 KB) 2. The Data set for Classification problem.mp4 (21.9 MB) 2. The Data set for Classification problem.srt (2.4 KB) 3. Building a classification Tree in R.mp4 (100.1 MB) 3. Building a classification Tree in R.srt (11.9 KB) 4. Advantages and Disadvantages of Decision Trees.mp4 (7.8 MB) 4. Advantages and Disadvantages of Decision Trees.srt (2.2 KB) 15. Ensemble technique 1 - Bagging 1. Bagging.mp4 (32.3 MB) 1. Bagging.srt (7.6 KB) 2. Bagging in R.mp4 (69.3 MB) 2. Bagging in R.srt (8.2 KB) 16. Ensemble technique 2 - Random Forest 1. Random Forest technique.mp4 (21.4 MB) 1. Random Forest technique.srt (5.1 KB) 2. Random Forest in R.mp4 (37.4 MB) 2. Random Forest in R.srt (5.6 KB) 17. Ensemble technique 3 - GBM, AdaBoost and XGBoost 1. Boosting techniques.mp4 (34.4 MB) 1. Boosting techniques.srt (9.6 KB) 2. Gradient Boosting in R.mp4 (78.6 MB) 2. Gradient Boosting in R.srt (9.6 KB) 3. AdaBoosting in R.mp4 (103.0 MB) 3. AdaBoosting in R.srt (12.2 KB) 4. XGBoosting in R.mp4 (186.5 MB) 4. XGBoosting in R.srt (21.1 KB) 18. Support Vector Machines 1. Introduction to SVM.mp4 (21.6 MB) 1. Introduction to SVM.srt (3.2 KB) 2. The Concept of a Hyperplane.mp4 (35.3 MB) 2. The Concept of a Hyperplane.srt (6.2 KB) 3. Maximum Margin Classifier.mp4 (26.2 MB) 3. Maximum Margin Classifier.srt (4.4 KB) 4. Limitations of Maximum Margin Classifier.mp4 (12.5 MB) 4. Limitations of Maximum Margin Classifier.srt (3.1 KB) 19. Support Vector Classifier 1. Support Vector classifiers.mp4 (64.1 MB) 1. Support Vector classifiers.srt (12.5 KB) 2. Limitations of Support Vector Classifiers.mp4 (13.0 MB) 2. Limitations of Support Vector Classifiers.srt (1.9 KB) 2. Setting up R Studio and R crash course 1. Installing R and R studio.mp4 (40.8 MB) 1. Installing R and R studio.srt (7.4 KB) 2. This is a milestone!.mp4 (20.7 MB) 2. This is a milestone!.srt (3.9 KB) 3. Basics of R and R studio.mp4 (48.0 MB) 3. Basics of R and R studio.srt (14.4 KB) 4. Packages in R.mp4 (98.5 MB) 4. Packages in R.srt (14.6 KB) 5. Inputting data part 1 Inbuilt datasets of R.mp4 (46.1 MB) 5. Inputting data part 1 Inbuilt datasets of R.srt (5.6 KB) 6. Inputting data part 2 Manual data entry.mp4 (30.8 MB) 6. Inputting data part 2 Manual data entry.srt (3.7 KB) 7. Inputting data part 3 Importing from CSV or Text files.mp4 (69.0 MB) 7. Inputting data part 3 Importing from CSV or Text files.srt (8.4 KB) 7.1 Customer.csv (64.0 KB) 7.2 Product.txt (139.5 KB) 8. Creating Barplots in R.mp4 (117.2 MB) 8. Creating Barplots in R.srt (18.3 KB) 9. Creating Histograms in R files
Added:	2023-05-12 15:03:36
Language:	English
Peers:	Seeders : 18 , Leechers : 10
Tags:	Udemy free course download fcs
Release name:	Udemy - Complete Machine Learning with R Studio - ML for 2023 [FCS]
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