Setting Up R and Getting Started
I. Introduction:
In this lecture, we will walk through the steps of setting up the R environment and getting it ready for use. The goal is to ensure everyone has the necessary tools and knowledge to start working with R and explore its application to word embeddings, as discussed in the previous lecture.
II. Objectives:
Understand how to install R and RStudio. Learn to install and load R packages. Understand the basic structure and syntax of R. III. Installation of R:
A. Installing R:
Visit and download the appropriate version of R for your operating system (Windows/Mac/Linux). Run the downloaded file and follow the installation prompts. B. Installing RStudio (Optional but Recommended):
Go to the RStudio website: Visit and download the RStudio Desktop (Open Source License). Run the downloaded file and follow the installation prompts. IV. Setting Up the R Environment:
A. Launch R/RStudio:
Open R or RStudio on your computer. B. Installing Packages:
Use the install.packages("packageName") function to install a package. For example: RCopy code
install.packages("textTinyR") install.packages("ggplot2")
Use the library(packageName) function to load a package. For example: RCopy code
library(textTinyR) library(ggplot2)
V. Getting Familiar with R Syntax:
A. Basic Operations:
Perform basic arithmetic operations and assign values to variables. RCopy code
x <- 5 + 3 # Assigns the value 8 to x
B. Functions:
Understand the usage of functions. RCopy code
print(x) # Outputs the value of x
C. Working with Vectors and Data Frames:
Create and manipulate vectors and data frames. RCopy code
v <- c(1, 2, 3) # Creates a vector v with values 1, 2, and 3
VI. Hands-On Example:
Let’s create word embeddings using the textTinyR package as we learned in the previous lecture. RCopy code
# Load the package
library(textTinyR)
# Example sentences
sentences <- c("I love machine learning", "Word embeddings are fascinating")
# Create word embeddings
embeddings <- WORD2VEC(sentences = sentences, method = 'skipgram')
VII. Conclusion:
Congratulations on setting up your R environment! You're now ready to embark on your journey to explore and understand word embeddings and other fascinating areas of data science and machine learning. Remember, the more you practice, the more you'll learn and discover about the capabilities of R. Happy coding!