FTUForum com UDEMY Beginner to Advanced Guide on Machine Learning with Tool FTU

FTUForum com UDEMY Beginner to Advanced Guide on Machine Learning with Tool FTU

Name	[FTUForum.com] [UDEMY] Beginner to Advanced Guide on Machine Learning with R Tool [FTU]	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	355.0 MB
Total Files	99
Hash	08FA1CC0FCE7C5B246C1A62023A81991E9D164E5

/0. Websites you may like/
1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url	0.3 KB
2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url	0.3 KB
3. (NulledPremium.com) Download Cracked Website Themes, Plugins, Scripts And Stock Images.url	0.2 KB
4. (FTUApps.com) Download Cracked Developers Applications For Free.url	0.2 KB
5. (Discuss.FTUForum.com) FTU Discussion Forum.url	0.3 KB
How you can help Team-FTU.txt	0.2 KB
/1. Module-1 Introduction to Course/
1. 1.1 Introduction to the Course.mp4	18.5 MB
1. 1.1 Introduction to the Course.vtt	2.6 KB
2. 1.2 Pre-Requisite.mp4	3.7 MB
2. 1.2 Pre-Requisite.vtt	0.8 KB
3. 1.3 What you will Learn.mp4	3.9 MB
3. 1.3 What you will Learn.vtt	1.9 KB
4. 1.4 Techniques of Machine Learning.mp4	6.4 MB
4. 1.4 Techniques of Machine Learning.vtt	4.3 KB
/2. Module-2 Introduction to validation and its Methods/
1. 2.1 Introduction to Cross Validation.mp4	3.6 MB
1. 2.1 Introduction to Cross Validation.vtt	2.4 KB
2. 2.2 Cross Validation Method.mp4	5.6 MB
2. 2.2 Cross Validation Method.vtt	3.7 KB
3.1 Programs.zip.zip	11.2 KB
3. 2.3 Caret package.mp4	16.5 MB
3. 2.3 Caret package.vtt	8.4 KB
/3. Module-3 Classification/
1. 3.1 Introduction to Classification.mp4	3.4 MB
1. 3.1 Introduction to Classification.vtt	1.9 KB
2. 3.2 KNN- K Nearest Neighbors.mp4	6.4 MB
2. 3.2 KNN- K Nearest Neighbors.vtt	3.7 KB
3.1 Programs.zip.zip	11.2 KB
3. 3.3 Implementation of KNN Algorithm.mp4	15.4 MB
3. 3.3 Implementation of KNN Algorithm.vtt	6.7 KB
4. 3.4 Naive-Bayes Classifier.mp4	5.3 MB
4. 3.4 Naive-Bayes Classifier.vtt	3.1 KB
5.1 Programs.zip.zip	11.2 KB
5. 3.5 Implementation of Naive-Bayes Classifier.mp4	35.7 MB
5. 3.5 Implementation of Naive-Bayes Classifier.vtt	15.2 KB
6. 3.6 Linear Discriminant Analysis.mp4	2.5 MB
6. 3.6 Linear Discriminant Analysis.vtt	1.3 KB
7.1 Programs.zip.zip	11.2 KB
7. 3.7 Implementation of Linear Discriminant Analysis.mp4	6.7 MB
7. 3.7 Implementation of Linear Discriminant Analysis.vtt	3.0 KB
/4. Module-4 Black Box Method-Neural network and SVM/
1. 4.1 Introduction to Artificial Neural Network.mp4	3.3 MB
1. 4.1 Introduction to Artificial Neural Network.vtt	1.7 KB
2. 4.2 Conceptualizing of Neural Network.mp4	5.6 MB
2. 4.2 Conceptualizing of Neural Network.vtt	2.5 KB
3.1 Programs.zip.zip	11.2 KB
3. 4.3 Implement Neural Network in R.mp4	12.9 MB
3. 4.3 Implement Neural Network in R.vtt	5.1 KB
4. 4.4 Back Propagation.mp4	2.8 MB
4. 4.4 Back Propagation.vtt	1.7 KB
5.1 Programs.zip.zip	11.2 KB
5. 4.5 Implementation of Back Propagation Network.mp4	4.5 MB
5. 4.5 Implementation of Back Propagation Network.vtt	1.6 KB
6. 4.6 Introduction to Support Vector Machine.mp4	5.2 MB
6. 4.6 Introduction to Support Vector Machine.vtt	2.9 KB
7.1 Programs.zip.zip	11.2 KB
7. 4.7 Implementation of SVM in R.mp4	9.3 MB
7. 4.7 Implementation of SVM in R.vtt	3.9 KB
/5. Module-5 Tree Based Models/
1. 5.1 Decision Tree.mp4	5.1 MB
1. 5.1 Decision Tree.vtt	2.7 KB
2.1 Programs.zip.zip	11.2 KB
2. 5.2 Implementation of Decision Tree.mp4	9.1 MB
2. 5.2 Implementation of Decision Tree.vtt	3.8 KB
3.1 Programs.zip.zip	11.2 KB
3. 5.3 Bagging.mp4	8.1 MB
3. 5.3 Bagging.vtt	3.7 KB
4.1 Programs.zip.zip	11.2 KB
4. 5.4 Boosting.mp4	11.3 MB
4. 5.4 Boosting.vtt	6.1 KB
5. 5.5 Introduction to Random Forest.mp4	4.3 MB
5. 5.5 Introduction to Random Forest.vtt	2.4 KB
6.1 Programs.zip.zip	11.2 KB
6. 5.6 Implementation of Random Forest.mp4	7.8 MB
6. 5.6 Implementation of Random Forest.vtt	3.4 KB
/6. Module-6 Clustering/
1. 6.1 Introduction to Clustering.mp4	3.0 MB
1. 6.1 Introduction to Clustering.vtt	1.8 KB
2. 6.2 K-Means Clustering.mp4	11.8 MB
2. 6.2 K-Means Clustering.vtt	7.8 KB
3.1 Programs.zip.zip	11.2 KB
3. 6.3 Implementation of K-Means Clustering.mp4	8.5 MB
3. 6.3 Implementation of K-Means Clustering.vtt	3.4 KB
4.1 Programs.zip.zip	11.2 KB
4. 6.4 Hierarchical Clustering.mp4	7.5 MB
4. 6.4 Hierarchical Clustering.vtt	3.5 KB
/7. Module-7 Regression/
1. 7.1 Predicting with Linear Regression.mp4	4.8 MB
1. 7.1 Predicting with Linear Regression.vtt	2.6 KB
2.1 Programs.zip.zip	11.2 KB
2. 7.2 Implementation of Linear Regression.mp4	12.9 MB
2. 7.2 Implementation of Linear Regression.vtt	6.0 KB
3.1 Programs.zip.zip	11.2 KB
3. 7.3 Multiple Covariates Regression.mp4	10.8 MB
3. 7.3 Multiple Covariates Regression.vtt	5.3 KB
4. 7.4 Logistic Regression.mp4	4.9 MB
4. 7.4 Logistic Regression.vtt	2.7 KB
5.1 Programs.zip.zip	11.2 KB
5. 7.5 Implementation of Logistic Regression.mp4	6.9 MB
5. 7.5 Implementation of Logistic Regression.vtt	3.2 KB
6. 7.6 Forecasting.mp4	20.8 MB
6. 7.6 Forecasting.vtt	3.0 KB
7.1 Programs.zip.zip	11.2 KB
7. 7.7 Implementation of Forecasting.mp4	40.0 MB
7. 7.7 Implementation of Forecasting.vtt	2.7 KB
Total files 99