ExpiredMachine learning with R (RF, Adabost.M1, DT, NB, LR, NN)

FREE 34
Udemy

Machine learning with R (RF, Adabost.M1, DT, NB, LR, NN)

Requirements
  • No Prior programing knowledge is required. However a minimum knowledge of any programming and basic statistics is a plus
Description
  • How to download and install R
  • How to set your working directory import your data and detect rows containing missing values 
  • For binary classification
  1. Training and prediction using the Random Forest model , prediction accuracy, Confusion matrix  and confidence interval 
  2. Training and prediction using the  Adabost.M1 model , prediction accuracy, Confusion matrix and confidence interval 
  3. Training and prediction using the Decision Tree model , prediction accuracy, Confusion matrix and confidence interval
  4. Training and prediction using the logistic regression model, prediction accuracy, confusion matrix and confidence interval 
  5. Training and prediction using the Naive Bayes model, prediction accuracy, confusion matrix and confidence interval 
  6. Training and prediction using the Neural Network model , prediction  accuracy, confusion matrix and confidence interval 
  7. Training and prediction using the Convolutional neural network (KNN) , prediction accuracy, confusion matrix and confidence interval 
  • How to combine models to predict 
  • Missing values treatment ,variables selection and prediction using a linear regression model   
  • K mean Clustering 
Who this course is for:
  • If you are interested on predictive analytic , then this course is a right fit for you.


  • Register New Account
    Reset Password