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Category:
Language:
English
Total Size:
5.9 GB
Info Hash:
0D002469C6F8295EC8B03A22F6A0B53029B0AF10
Added By:
Added:
Oct. 25, 2023, 7:49 p.m.
Stats:
|
(Last updated: May 14, 2025, 6:01 p.m.)
| File | Size |
|---|---|
| [GigaCourse.Com].url | 49 bytes |
| 001 Introduction.mp4 | 21.2 MB |
| 002 Course Resources.html | 1.2 KB |
| 001 Installing R and R studio.mp4 | 40.8 MB |
| 002 This is a milestone!.mp4 | 20.7 MB |
| 003 Basics of R and R studio.mp4 | 48.0 MB |
| 004 Packages in R.mp4 | 98.5 MB |
| 005 Inputting data part 1_ Inbuilt datasets of R.mp4 | 46.1 MB |
| 006 Inputting data part 2_ Manual data entry.mp4 | 30.8 MB |
| 007 Inputting data part 3_ Importing from CSV or Text files.mp4 | 69.0 MB |
| 008 Creating Barplots in R.mp4 | 117.2 MB |
| 009 Creating Histograms in R.mp4 | 51.3 MB |
| 009 Customer.csv | 64.0 KB |
| 009 Product.txt | 137.7 KB |
| 001 Types of Data.mp4 | 21.8 MB |
| 002 Types of Statistics.mp4 | 10.9 MB |
| 003 Describing the data graphically.mp4 | 65.4 MB |
| 004 Measures of Centers.mp4 | 38.5 MB |
| 005 Measures of Dispersion.mp4 | 22.8 MB |
| 001 Introduction to Machine Learning.mp4 | 123.3 MB |
| 002 Building a Machine Learning Model.mp4 | 44.9 MB |
| 001 Gathering Business Knowledge.mp4 | 25.0 MB |
| 002 Data Exploration.mp4 | 23.3 MB |
| 003 The Data and the Data Dictionary.mp4 | 78.3 MB |
| 004 Importing the dataset into R.mp4 | 15.9 MB |
| 005 Univariate Analysis and EDD.mp4 | 27.2 MB |
| 006 EDD in R.mp4 | 112.0 MB |
| 007 Outlier Treatment.mp4 | 27.7 MB |
| 008 Outlier Treatment in R.mp4 | 37.8 MB |
| 009 Missing Value imputation.mp4 | 27.4 MB |
| 010 Missing Value imputation in R.mp4 | 31.7 MB |
| 011 Seasonality in Data.mp4 | 20.8 MB |
| 012 Bi-variate Analysis and Variable Transformation.mp4 | 113.1 MB |
| 013 Variable transformation in R.mp4 | 67.6 MB |
| 014 Non Usable Variables.mp4 | 23.7 MB |
| 015 Dummy variable creation_ Handling qualitative data.mp4 | 40.5 MB |
| 016 Dummy variable creation in R.mp4 | 52.2 MB |
| 017 Correlation Matrix and cause-effect relationship.mp4 | 80.8 MB |
| 018 Correlation Matrix in R.mp4 | 94.9 MB |
| [GigaCourse.Com].url | 49 bytes |
| 001 The problem statement.mp4 | 10.6 MB |
| 002 Basic equations and Ordinary Least Squared (OLS) method.mp4 | 49.9 MB |
| 003 Assessing Accuracy of predicted coefficients.mp4 | 103.9 MB |
| 004 Assessing Model Accuracy - RSE and R squared.mp4 | 49.5 MB |
| 005 Simple Linear Regression in R.mp4 | 50.5 MB |
| 006 Multiple Linear Regression.mp4 | 38.7 MB |
| 007 The F - statistic.mp4 | 63.8 MB |
| 008 Interpreting result for categorical Variable.mp4 | 26.9 MB |
| 009 Multiple Linear Regression in R.mp4 | 72.8 MB |
| 010 Test-Train split.mp4 | 48.8 MB |
| 011 Bias Variance trade-off.mp4 | 29.4 MB |
| 012 More about test-train split.html | 1.4 KB |
| 013 Test-Train Split in R.mp4 | 90.9 MB |
| 001 Linear models other than OLS.mp4 | 19.0 MB |
| 002 Subset Selection techniques.mp4 | 86.7 MB |
| 003 Subset selection in R.mp4 | 76.6 MB |
| 004 Shrinkage methods - Ridge Regression and The Lasso.mp4 | 38.4 MB |
| 005 Ridge regression and Lasso in R.mp4 | 124.0 MB |
| 001 The Data and the Data Dictionary.mp4 | 87.4 MB |
| 002 Importing the dataset into R.mp4 | 16.3 MB |
| 003 EDD in R.mp4 | 77.8 MB |
| 004 Outlier Treatment in R.mp4 | 31.2 MB |
| 005 Missing Value imputation in R.mp4 | 23.4 MB |
| 006 Variable transformation in R.mp4 | 46.5 MB |
| 007 Dummy variable creation in R.mp4 | 52.5 MB |
| 001 Three Classifiers and the problem statement.mp4 | 22.8 MB |
| 002 Why can't we use Linear Regression_.mp4 | 20.2 MB |
| 001 Logistic Regression.mp4 | 38.8 MB |
| 002 Training a Simple Logistic model in R.mp4 | 31.0 MB |
| 003 Results of Simple Logistic Regression.mp4 | 30.9 MB |
| 004 Logistic with multiple predictors.mp4 | 9.9 MB |
| 005 Training multiple predictor Logistic model in R.mp4 | 18.3 MB |
| 006 Confusion Matrix.mp4 | 26.6 MB |
| 007 Evaluating Model performance.mp4 | 42.5 MB |
| 008 Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4 | 66.1 MB |
| [GigaCourse.Com].url | 49 bytes |
| 001 Linear Discriminant Analysis.mp4 | 48.4 MB |
| 002 Linear Discriminant Analysis in R.mp4 | 89.5 MB |
| 001 Test-Train Split.mp4 | 45.4 MB |
| 002 Test-Train Split in R.mp4 | 90.2 MB |
| 003 K-Nearest Neighbors classifier.mp4 | 83.3 MB |
| 004 K-Nearest Neighbors in R.mp4 | 79.6 MB |
| 001 Understanding the results of classification models.mp4 | 45.8 MB |
| 002 Summary of the three models.mp4 | 25.1 MB |
| 001 Basics of Decision Trees.mp4 | 50.6 MB |
| 002 Understanding a Regression Tree.mp4 | 52.2 MB |
| 003 The stopping criteria for controlling tree growth.mp4 | 16.5 MB |
| 004 The Data set for this part.mp4 | 42.0 MB |
| 005 Course resources_ Notes and Datasets.html | 990 bytes |
| 006 Importing the Data set into R.mp4 | 51.8 MB |
| 007 Splitting Data into Test and Train Set in R.mp4 | 52.6 MB |
| 008 Building a Regression Tree in R.mp4 | 121.9 MB |
| 009 Pruning a tree.mp4 | 22.2 MB |
| 010 Pruning a Tree in R.mp4 | 97.0 MB |
| 00_Intro.pdf | 334.9 KB |
| 01_basics.pdf | 166.0 KB |
| 02_Decision Tree.pdf | 205.8 KB |
| 03_Concepts.pdf | 221.7 KB |
| 04_Stop_condition.pdf | 154.8 KB |
| 05_Prune.pdf | 228.5 KB |
| 06_Decision Tree - Class.pdf | 209.2 KB |
| 07_Bagging.pdf | 303.7 KB |
| 08_Random_Forest.pdf | 168.4 KB |
| 09_Boosting.pdf | 178.0 KB |
| 10_Adv_disadv.pdf | 145.5 KB |
| Movie_classification.csv | 54.3 KB |
| Movie_regression.csv | 53.3 KB |
| tree_R.R | 7.5 KB |
| 001 Classification Trees.mp4 | 33.0 MB |
| 002 The Data set for Classification problem.mp4 | 21.9 MB |
| 003 Building a classification Tree in R.mp4 | 100.1 MB |
| 004 Advantages and Disadvantages of Decision Trees.mp4 | 7.8 MB |
| 001 Bagging.mp4 | 32.3 MB |
| 002 Bagging in R.mp4 | 69.3 MB |
| 001 Random Forest technique.mp4 | 21.4 MB |
| 002 Random Forest in R.mp4 | 37.4 MB |
| [GigaCourse.Com].url | 49 bytes |
| 001 Boosting techniques.mp4 | 34.4 MB |
| 002 Gradient Boosting in R.mp4 | 78.6 MB |
| 003 AdaBoosting in R.mp4 | 103.0 MB |
| 004 XGBoosting in R.mp4 | 186.5 MB |
| 001 Content flow.mp4 | 9.8 MB |
| 002 The Concept of a Hyperplane.mp4 | 35.3 MB |
| 003 Maximum Margin Classifier.mp4 | 26.2 MB |
| 004 Limitations of Maximum Margin Classifier.mp4 | 12.5 MB |
| 001 Support Vector classifiers.mp4 | 64.1 MB |
| 002 Limitations of Support Vector Classifiers.mp4 | 13.0 MB |
| 001 Kernel Based Support Vector Machines.mp4 | 45.7 MB |
| 001 The Data set for the Classification problem.mp4 | 22.0 MB |
| 002 Course resources_ Notes and Datasets.html | 963 bytes |
| 003 Importing Data into R.mp4 | 65.3 MB |
| 004 Test-Train Split.mp4 | 59.4 MB |
| 005 Classification SVM model using Linear Kernel.mp4 | 166.9 MB |
| 006 Hyperparameter Tuning for Linear Kernel.mp4 | 70.4 MB |
| 007 Polynomial Kernel with Hyperparameter Tuning.mp4 | 98.7 MB |
| 008 Radial Kernel with Hyperparameter Tuning.mp4 | 67.4 MB |
| 009 The Data set for the Regression problem.mp4 | 41.8 MB |
| 010 SVM based Regression Model in R.mp4 | 124.0 MB |
| 00000_Intro.pdf | 334.9 KB |
| 01_SVM_flow.pdf | 143.9 KB |
| 02_Max_Mar_Class.pdf | 287.9 KB |
| 03_Max_Mar_Class_LIMIT.pdf | 328.7 KB |
| 04_support_v_class.pdf | 189.0 KB |
| 05_Support_vec_class_LIMIT.pdf | 198.7 KB |
| 06_SVM.pdf | 360.4 KB |
| Movie_classification.csv | 54.3 KB |
| Movie_regression.csv | 53.3 KB |
| SVM_R.R | 3.0 KB |
| [GigaCourse.Com].url | 49 bytes |
| 001 The final milestone!.mp4 | 11.9 MB |
| 002 Congratulations & About your certificate.html | 2.7 KB |
| [GigaCourse.Com].url | 49 bytes |
Name
DL
Uploader
Size
S/L
Added
-
713.3 MB
[0
/
3]
2025-02-21
| Uploaded by freecoursewb | Size 713.3 MB | Health [ 0 /3 ] | Added 2025-02-21 |
-
1.8 GB
[72
/
10]
2025-01-13
| Uploaded by FreeCourseWeb | Size 1.8 GB | Health [ 72 /10 ] | Added 2025-01-13 |
NOTE
SOURCE: Udemy Complete Machine Learning with R Studio ML for 2021 Giga Course
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