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Complete Machine Learning with R Studio - ML for 2021

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Complete Machine Learning with R Studio - ML for 2021

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文件列表

  • 18 Ensemble technique 3 - GBM, AdaBoost and XGBoost/004 XGBoosting in R.mp4 195.5 MB
  • 22 Creating Support Vector Machine Model in R/005 Classification SVM model using Linear Kernel.mp4 175.0 MB
  • 07 Regression models other than OLS/005 Ridge regression and Lasso in R.mp4 130.0 MB
  • 22 Creating Support Vector Machine Model in R/010 SVM based Regression Model in R.mp4 130.0 MB
  • 04 Intorduction to Machine Learning/001 Introduction to Machine Learning.mp4 129.3 MB
  • 14 Simple Decision Trees/008 Building a Regression Tree in R.mp4 127.8 MB
  • 02 Setting up R Studio and R crash course/008 Creating Barplots in R.mp4 122.9 MB
  • 05 Data Preprocessing for Regression Analysis/012 Bi-variate Analysis and Variable Transformation.mp4 118.6 MB
  • 05 Data Preprocessing for Regression Analysis/006 EDD in R.mp4 117.4 MB
  • 06 Linear Regression Model/003 Assessing Accuracy of predicted coefficients.mp4 108.9 MB
  • 18 Ensemble technique 3 - GBM, AdaBoost and XGBoost/003 AdaBoosting in R.mp4 108.0 MB
  • 15 Simple Classification Tree/003 Building a classification Tree in R.mp4 104.9 MB
  • 22 Creating Support Vector Machine Model in R/007 Polynomial Kernel with Hyperparameter Tuning.mp4 103.4 MB
  • 02 Setting up R Studio and R crash course/004 Packages in R.mp4 103.3 MB
  • 14 Simple Decision Trees/010 Pruning a Tree in R.mp4 101.7 MB
  • 05 Data Preprocessing for Regression Analysis/018 Correlation Matrix in R.mp4 99.5 MB
  • 06 Linear Regression Model/013 Test-Train Split in R.mp4 95.3 MB
  • 12 K-Nearest Neighbors/002 Test-Train Split in R.mp4 94.5 MB
  • 11 Linear Discriminant Analysis/002 Linear Discriminant Analysis in R.mp4 93.8 MB
  • 08 Classification Models_ Data Preparation/001 The Data and the Data Dictionary.mp4 91.7 MB
  • 07 Regression models other than OLS/002 Subset Selection techniques.mp4 90.9 MB
  • 12 K-Nearest Neighbors/003 K-Nearest Neighbors classifier.mp4 87.3 MB
  • 05 Data Preprocessing for Regression Analysis/017 Correlation Matrix and cause-effect relationship.mp4 84.8 MB
  • 12 K-Nearest Neighbors/004 K-Nearest Neighbors in R.mp4 83.5 MB
  • 18 Ensemble technique 3 - GBM, AdaBoost and XGBoost/002 Gradient Boosting in R.mp4 82.4 MB
  • 05 Data Preprocessing for Regression Analysis/003 The Data and the Data Dictionary.mp4 82.1 MB
  • 08 Classification Models_ Data Preparation/003 EDD in R.mp4 81.6 MB
  • 07 Regression models other than OLS/003 Subset selection in R.mp4 80.3 MB
  • 06 Linear Regression Model/009 Multiple Linear Regression in R.mp4 76.4 MB
  • 22 Creating Support Vector Machine Model in R/006 Hyperparameter Tuning for Linear Kernel.mp4 73.8 MB
  • 16 Ensemble technique 1 - Bagging/002 Bagging in R.mp4 72.7 MB
  • 02 Setting up R Studio and R crash course/007 Inputting data part 3_ Importing from CSV or Text files.mp4 72.3 MB
  • 05 Data Preprocessing for Regression Analysis/013 Variable transformation in R.mp4 70.9 MB
  • 22 Creating Support Vector Machine Model in R/008 Radial Kernel with Hyperparameter Tuning.mp4 70.6 MB
  • 10 Logistic Regression/008 Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4 69.3 MB
  • 03 Basics of Statistics/003 Describing the data graphically.mp4 68.5 MB
  • 22 Creating Support Vector Machine Model in R/003 Importing Data into R.mp4 68.5 MB
  • 20 Support Vector Classifier/001 Support Vector classifiers.mp4 67.2 MB
  • 06 Linear Regression Model/007 The F - statistic.mp4 66.9 MB
  • 22 Creating Support Vector Machine Model in R/004 Test-Train Split.mp4 62.2 MB
  • 14 Simple Decision Trees/007 Splitting Data into Test and Train Set in R.mp4 55.1 MB
  • 08 Classification Models_ Data Preparation/007 Dummy variable creation in R.mp4 55.0 MB
  • 05 Data Preprocessing for Regression Analysis/016 Dummy variable creation in R.mp4 54.8 MB
  • 14 Simple Decision Trees/002 Understanding a Regression Tree.mp4 54.7 MB
  • 14 Simple Decision Trees/006 Importing the Data set into R.mp4 54.3 MB
  • 02 Setting up R Studio and R crash course/009 Creating Histograms in R.mp4 53.8 MB
  • 14 Simple Decision Trees/001 Basics of Decision Trees.mp4 53.0 MB
  • 06 Linear Regression Model/005 Simple Linear Regression in R.mp4 52.9 MB
  • 06 Linear Regression Model/002 Basic equations and Ordinary Least Squared (OLS) method.mp4 52.3 MB
  • 06 Linear Regression Model/004 Assessing Model Accuracy - RSE and R squared.mp4 51.9 MB
  • 06 Linear Regression Model/010 Test-Train split.mp4 51.1 MB
  • 11 Linear Discriminant Analysis/001 Linear Discriminant Analysis.mp4 50.7 MB
  • 02 Setting up R Studio and R crash course/003 Basics of R and R studio.mp4 50.3 MB
  • 08 Classification Models_ Data Preparation/006 Variable transformation in R.mp4 48.7 MB
  • 02 Setting up R Studio and R crash course/005 Inputting data part 1_ Inbuilt datasets of R.mp4 48.4 MB
  • 13 Comparing results from 3 models/001 Understanding the results of classification models.mp4 48.0 MB
  • 21 Support Vector Machines/001 Kernel Based Support Vector Machines.mp4 47.9 MB
  • 12 K-Nearest Neighbors/001 Test-Train Split.mp4 47.6 MB
  • 04 Intorduction to Machine Learning/002 Building a Machine Learning Model.mp4 47.1 MB
  • 10 Logistic Regression/007 Evaluating Model performance.mp4 44.6 MB
  • 14 Simple Decision Trees/004 The Data set for this part.mp4 44.0 MB
  • 22 Creating Support Vector Machine Model in R/009 The Data set for the Regression problem.mp4 43.8 MB
  • 02 Setting up R Studio and R crash course/001 Installing R and R studio.mp4 42.7 MB
  • 05 Data Preprocessing for Regression Analysis/015 Dummy variable creation_ Handling qualitative data.mp4 42.5 MB
  • 10 Logistic Regression/001 Logistic Regression.mp4 40.7 MB
  • 06 Linear Regression Model/006 Multiple Linear Regression.mp4 40.6 MB
  • 03 Basics of Statistics/004 Measures of Centers.mp4 40.4 MB
  • 07 Regression models other than OLS/004 Shrinkage methods - Ridge Regression and The Lasso.mp4 40.3 MB
  • 05 Data Preprocessing for Regression Analysis/008 Outlier Treatment in R.mp4 39.7 MB
  • 17 Ensemble technique 2 - Random Forest/002 Random Forest in R.mp4 39.2 MB
  • 19 Maximum Margin Classifier/002 The Concept of a Hyperplane.mp4 37.0 MB
  • 18 Ensemble technique 3 - GBM, AdaBoost and XGBoost/001 Boosting techniques.mp4 36.0 MB
  • 15 Simple Classification Tree/001 Classification Trees.mp4 34.6 MB
  • 16 Ensemble technique 1 - Bagging/001 Bagging.mp4 33.9 MB
  • 05 Data Preprocessing for Regression Analysis/010 Missing Value imputation in R.mp4 33.2 MB
  • 08 Classification Models_ Data Preparation/004 Outlier Treatment in R.mp4 32.8 MB
  • 10 Logistic Regression/002 Training a Simple Logistic model in R.mp4 32.5 MB
  • 10 Logistic Regression/003 Results of Simple Logistic Regression.mp4 32.4 MB
  • 02 Setting up R Studio and R crash course/006 Inputting data part 2_ Manual data entry.mp4 32.3 MB
  • 06 Linear Regression Model/011 Bias Variance trade-off.mp4 30.8 MB
  • 05 Data Preprocessing for Regression Analysis/007 Outlier Treatment.mp4 29.0 MB
  • 05 Data Preprocessing for Regression Analysis/009 Missing Value imputation.mp4 28.7 MB
  • 05 Data Preprocessing for Regression Analysis/005 Univariate Analysis and EDD.mp4 28.5 MB
  • 06 Linear Regression Model/008 Interpreting result for categorical Variable.mp4 28.2 MB
  • 10 Logistic Regression/006 Confusion Matrix.mp4 27.8 MB
  • 19 Maximum Margin Classifier/003 Maximum Margin Classifier.mp4 27.4 MB
  • 13 Comparing results from 3 models/002 Summary of the three models.mp4 26.3 MB
  • 05 Data Preprocessing for Regression Analysis/001 Gathering Business Knowledge.mp4 26.2 MB
  • 05 Data Preprocessing for Regression Analysis/014 Non Usable Variables.mp4 24.9 MB
  • 08 Classification Models_ Data Preparation/005 Missing Value imputation in R.mp4 24.5 MB
  • 05 Data Preprocessing for Regression Analysis/002 Data Exploration.mp4 24.4 MB
  • 03 Basics of Statistics/005 Measures of Dispersion.mp4 24.0 MB
  • 09 The Three classification models/001 Three Classifiers and the problem statement.mp4 23.9 MB
  • 14 Simple Decision Trees/009 Pruning a tree.mp4 23.3 MB
  • 22 Creating Support Vector Machine Model in R/001 The Data set for the Classification problem.mp4 23.0 MB
  • 15 Simple Classification Tree/002 The Data set for Classification problem.mp4 23.0 MB
  • 03 Basics of Statistics/001 Types of Data.mp4 22.8 MB
  • 17 Ensemble technique 2 - Random Forest/001 Random Forest technique.mp4 22.5 MB
  • 01 Welcome to the course/001 Introduction.mp4 22.2 MB
  • 05 Data Preprocessing for Regression Analysis/011 Seasonality in Data.mp4 21.8 MB
  • 02 Setting up R Studio and R crash course/002 This is a milestone!.mp4 21.7 MB
  • 09 The Three classification models/002 Why can't we use Linear Regression_.mp4 21.2 MB
  • 07 Regression models other than OLS/001 Linear models other than OLS.mp4 19.9 MB
  • 10 Logistic Regression/005 Training multiple predictor Logistic model in R.mp4 19.2 MB
  • 14 Simple Decision Trees/003 The stopping criteria for controlling tree growth.mp4 17.3 MB
  • 08 Classification Models_ Data Preparation/002 Importing the dataset into R.mp4 17.1 MB
  • 05 Data Preprocessing for Regression Analysis/004 Importing the dataset into R.mp4 16.7 MB
  • 20 Support Vector Classifier/002 Limitations of Support Vector Classifiers.mp4 13.6 MB
  • 19 Maximum Margin Classifier/004 Limitations of Maximum Margin Classifier.mp4 13.1 MB
  • 23 Conclusion/001 The final milestone!.mp4 12.4 MB
  • 03 Basics of Statistics/002 Types of Statistics.mp4 11.5 MB
  • 06 Linear Regression Model/001 The problem statement.mp4 11.2 MB
  • 10 Logistic Regression/004 Logistic with multiple predictors.mp4 10.4 MB
  • 19 Maximum Margin Classifier/001 Content flow.mp4 10.2 MB
  • 15 Simple Classification Tree/004 Advantages and Disadvantages of Decision Trees.mp4 8.1 MB
  • 22 Creating Support Vector Machine Model in R/Files/06_SVM.pdf 369.0 kB
  • 14 Simple Decision Trees/Files/00_Intro.pdf 343.0 kB
  • 22 Creating Support Vector Machine Model in R/Files/00000_Intro.pdf 343.0 kB
  • 22 Creating Support Vector Machine Model in R/Files/03_Max_Mar_Class_LIMIT.pdf 336.6 kB
  • 14 Simple Decision Trees/Files/07_Bagging.pdf 311.0 kB
  • 22 Creating Support Vector Machine Model in R/Files/02_Max_Mar_Class.pdf 294.8 kB
  • 14 Simple Decision Trees/Files/05_Prune.pdf 234.0 kB
  • 14 Simple Decision Trees/Files/03_Concepts.pdf 227.0 kB
  • 14 Simple Decision Trees/Files/06_Decision Tree - Class.pdf 214.2 kB
  • 14 Simple Decision Trees/Files/02_Decision Tree.pdf 210.8 kB
  • 22 Creating Support Vector Machine Model in R/Files/05_Support_vec_class_LIMIT.pdf 203.5 kB
  • 22 Creating Support Vector Machine Model in R/Files/04_support_v_class.pdf 193.5 kB
  • 14 Simple Decision Trees/Files/09_Boosting.pdf 182.3 kB
  • 14 Simple Decision Trees/Files/08_Random_Forest.pdf 172.4 kB
  • 14 Simple Decision Trees/Files/01_basics.pdf 170.0 kB
  • 14 Simple Decision Trees/Files/04_Stop_condition.pdf 158.5 kB
  • 14 Simple Decision Trees/Files/10_Adv_disadv.pdf 149.0 kB
  • 22 Creating Support Vector Machine Model in R/Files/01_SVM_flow.pdf 147.4 kB
  • 02 Setting up R Studio and R crash course/009 Product.txt 142.8 kB
  • 02 Setting up R Studio and R crash course/009 Customer.csv 65.6 kB
  • 14 Simple Decision Trees/Files/Movie_classification.csv 55.6 kB
  • 22 Creating Support Vector Machine Model in R/Files/Movie_classification.csv 55.6 kB
  • 14 Simple Decision Trees/Files/Movie_regression.csv 54.5 kB
  • 22 Creating Support Vector Machine Model in R/Files/Movie_regression.csv 54.5 kB
  • 14 Simple Decision Trees/Files/tree_R.R 7.7 kB
  • 22 Creating Support Vector Machine Model in R/Files/SVM_R.R 3.1 kB
  • 23 Conclusion/002 Congratulations & About your certificate.html 2.8 kB
  • 06 Linear Regression Model/012 More about test-train split.html 1.5 kB
  • 01 Welcome to the course/002 Course Resources.html 1.2 kB
  • 14 Simple Decision Trees/005 Course resources_ Notes and Datasets.html 990 Bytes
  • 22 Creating Support Vector Machine Model in R/002 Course resources_ Notes and Datasets.html 963 Bytes
  • Downloaded from 1337x.html 543 Bytes

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