Introduction To Machine Learning Using R

Hi folks! it’s a pleasure for me to share my knowledge with you all. This is my first article in this C# Corner Community. I will be sharing my knowledge on Machine Learning and Deep Learning. In this article I will share my knowledge of kickstarting your career in Machine Learning using R. Still, this is my first article and I like to start from scratch,  so I hope this will be much more useful for beginners who are trying to start their career in Machine Learning.

Let's start With: What is Machine Learning & Why R Programming?

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn & improve from their experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

Introduction to Machine Learning Using R

How can you get started with ML?

  1. Use a Cloud-based or Mobile API (Vision, Natural Language, Etc.)
  2. Use an existing model architecture & retrain it in your dataset.
  3. Develop your own machine learning models for new problems.

The above-mentioned points are more flexible but it requires much more effort.

Why ML is Important in R?

  1. To solve interesting cases making Speech recognition & Machine translation Possible.
  2. The new search feature in Google Photos, which received broad acclaim.
  3. Recognizing pedestrians and other vehicles in self-driving cars.

Now Welcome to R Programming

Introduction to Machine Learning Using R

What Is R?

  1. A programming “environment”
  2. object-oriented
  3. similar to S-Plus
  4. Freeware(Open-source)
  5. provides calculations on matrices
  6. excellent graphics capabilities
  7. supported by a large user network (CRAN)

What is R Studio software & Prerequisites

  1. Program: R is a clear and accessible programming tool
  2. Transform: R is made up of a collection of libraries designed specifically for data science
  3. Discover: Investigate the data, refine your hypothesis and analyze them
  4. Model: R provides a wide array of tools to capture the right model for your data
  5. Communicate: Integrate codes, graphs, and outputs to a report with R Markdown or build Shiny apps to share with the world

Let’s take a look at the usage of R by Industry

Introduction to Machine Learning Using R

Why use R?

Introduction to Machine Learning Using R

What is R Not?

  1. A statistics software package
  2. Menu-driven
  3. Quick to learn
  4. A program with a complex graphical interface

Now let’s get a dive about how you can download & Install R. From the following link you can be able to download Comprehensive R Archive Network (CRAN) (niser.ac.in) CRAN

Installation of R

What will you need for installation?

The following requirements are needed for the installation of R with additional supports

  1. R Studio
  2. Anaconda (Data Science Toolkit)
  3. Anaconda Essentials for R

What is R studio?

  1. RStudio is an integrated development environment for R, a programming language for statistical computing and graphics.
  2. It’s an editor that supports direct code execution, and a variety of robust tools for plotting, viewing history, debugging, and managing your workspace.

What is Anaconda?

  1. Anaconda is an open-source-based data science toolkit that is based on python and R-language
  2. It contains the collection of packages that will be used for Machine based algorithms
  3. Download Link for Anaconda 3 from this link Anaconda

There is an alternate way of installing Conda essentials for R Programming by using cmdlets.

We can use either command prompt or PowerShell for installing Conda essentials by executing this command,

  • conda install r-essentials
  • conda install –c r rstudio

I will share a blog about installing the Conda Essentials by executing the above commands in the next article. I hope this article will be a useful one. Feel free to ask if you have any queries, until then stay tuned!.


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