Essential Machine Learning with R Training

Introduction:

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

Many industries working with large amounts of data have recognised the value of machine learning technology. By gleaning insights from this data, organisations are able to work more efficiently or gain an advantage over competitors.

In this basic machine learning course with R, you will learn the fundamental of machine learning using R. R is a good tool to learn machine learning due to its user friendliness and large community support.

Course Objectives:

  • Identify appropriate machine learning methods to address the problems and issues
  • Perform data analysis using machine learning methods
  • Draw inferences from the data analysis – Using R for machine learning

Duration

7 hours, 1 Day Course

Mode of Delivery

Classroom-based, Instructor-led Training

Course Outlines

  1. Introduction to Machine Learning
    1. What is Machine Learning
    2. Types of Machine Learning
    3. Supervised vs Unsupervised Learning
    4. Python vs R for Machine Learning
    5. Install R Machine Learning Package
  2. Data Preprocessing
    1. Sample Data
    2. Impute Missing Data
    3. Normalize Data
    4. Split Data
  3. Regression Methods
    1. What is Linear Regression
    2. Regularization – Bias vs Variance Tradeoff
    3. Lasso Regression
    4. Ridge Regression
  4. Classification Methods
    1. What is Classification
    2. Logistic Regression
    3. Gaussian Naive Bayes (GNB)
    4. K Nearest Neighbor (KNN)
    5. Support Vector Machine (SVM)
    6. Decision Tree
    7. Confusion Matrix
    8. ROC and AUC Analysis