Machine Learning,Udemy Coupon 100% Off,Udemy Free Courses

Data Science, Machine learning with R

17 May , 2018  

 

Requirements
  • No Prior programming knowledge 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 means Clustering 
Who is the target audience?
  • If you are interested in predictive analytics, then this course is a right fit for you.

 

Learn Data Science, Machine learning with R

 

 

 

 

, , ,


Join Our Social Network

Visit Us On FacebookVisit Us On GooglePlusVisit Us On Twitter