###### Preview this course

# Machine Learning with R

### Complete Machine Learning course covering Linear Regression, Logistic Regression, KNN, Decision Trees, SVM and XG Boost

~~$16~~ $8

Price

### Machine Learning with R

# What you'll learn

#### Introduction to R

Build a foundation for one of the fastest-growing programming language. Learn how to use R for Machine Learning

#### Application Based

Become job-ready with this application-based course. Apply what you learn and build real-life projects

#### Data Pre-Processing

Step by Step guide for data preparation covering outlier treatment, missing value imputation, variable transformation & correlation

#### Basic Machine Learning

Start you Machine Learning career with basic Linear Regression, Logistic Regression, LDA and KNN models

#### Advanced Machine Learning

Learn Advanced Machine Learning models such as Decision trees, Bagging, Boosting, XGBoost, Random Forest, SVM etc.

# Our Happy Students!

**

**

**

**

**5/5

#### Ankita Bagaria

I understood all the concepts. Really satisfied with the course. Specially the instructor really stick to the point and covered all the need full things promised.

**

**

**

**

**5/5

#### Nikhil Dethe

Good to start with the basics. Good explanation of r and RStudio and how to install. Only class to clearly explain that r is case-sensitive. Only class so far that explains what the ‘c’ and ‘:’ operators are called.

**

**

**

**

**5/5

#### Roger Holeywell

# Course Instructors

# Course Completion Certificateâ€‹

Once you successfully complete the course, Start-Tech Academy will provide you with an industry-recognized course completion certificate

#### Still confused? Download the complete course syllabus

# Course Content

** Introduction Setting up R Studio and R crash course Basics of Statistics Introduction to Machine Learning Data Preprocessing Linear Regression Classification Models: Data Preparation The Three classification models Logistic Regression Linear Discriminant Analysis (LDA) K-Nearest Neighbors classifier Comparing results from 3 models Simple Decision Trees Simple Classification Tree Ensemble technique 1 – Bagging Ensemble technique 2 – Random Forests Ensemble technique 3 – Boosting Maximum Margin Classifier Support Vector Classifier Support Vector Machines Creating Support Vector Machine Model in R Conclusion **

## Responses