R Programing - Advanced

2 Day Course

Time & Location

Contact us to Schedule Courses
Virtual Instructor Led Hands on Courses

About the Course

R is an open-source programming language used for statistical computing, data analysis, and graphics. It’s used by a growing number of business and data analysts, statisticians, engineers, and scientists. This is because it’s a language that many nonprogrammers can easily work with, naturally extending a skill set that is common to high-end Excel users. It also has a wide variety of packages for data mining and for optimizing models. It's the perfect tool for when you have a statistical, numerical, or probabilities problems based on real data and you’ve pushed Excel past its limits.

COURSE CONTENT

FUNCTIONAL PROGRAMMING

• Functionals

• Function factories

• Function operators

OBJECT-ORIENTED PROGRAMMING

• Base types

• S3

• R6

• S4

• Trade-offs

METAPROGRAMMING

• Big picture

• Expressions

• Quasiquotation

• Evaluation

• Translating R code

TECHNIQUES

• Debugging

• Measuring performance

• Improving performance

NEURAL NETWORK

• Introduction to neural network

• Forward Propagation and Back Propagation

• Activation Function

• Implementation of the neural network in R

• Use-cases of NN

• Pros and Cons

MACHINE LEARNING

SUPERVISED LEARNING I

• K-Nearest Neighbors

• Decision Trees

• Random Forests

• Reliability of Random Forests

• Advantages & Disadvantages of Decision Trees

SUPERVISED LEARNING II

• Regression Algorithms

• Model Evaluation

• Model Evaluation: Overfitting & Underfitting

• Understanding Different Evaluation Models

UNSUPERVISED LEARNING

• K-Means Clustering plus Advantages & Disadvantages

• Hierarchical Clustering plus Advantages & Disadvantages

• Measuring the Distances Between Clusters - Single Linkage Clustering

• Measuring the Distances Between Clusters - Algorithms for Hierarchy Clustering

• Density-Based Clustering

DIMENSIONALITY REDUCTION & COLLABORATIVE FILTERING

• Dimensionality Reduction: Feature Extraction & Selection

• Collaborative Filtering & Its Challenges

Register
Prix
Qté
Total
  • Course Participants
    $1,295
    +$168.35 HST
    $1,295
    +$168.35 HST
    0
    $0
Total$0

Share This Event