Review the pre-requisites for the course. Knowledge of these pre-requisites helps in better understanding of this course material.
- [Instructor] This course is about text analytics and predictions using R. It focuses on analytics and machine learning techniques specific to text. This course has examples in R, and we use RStudio. So, it's good to have some familiarity with these tools. You will need to download the latest version of R and RStudio to follow along. RStudio will not run without a compatible version of R installed. You can download R from the cran.r-project.org website. You can also download RStudio from the rstudio.com website. The examples in this course also pre-process text data before using them for analytics. Techniques used include stopword removal, stemming, n-grams, and tf-idf. If you are not familiar with these techniques, I recommend taking my other course on LinkedIn Learning called Text Processing with R. While the course focuses on using machine learning techniques, like clustering and classification for text mining, it does not delve deep into these concepts. Rather, it focuses on using these techniques for text-specific data.
- Creating a word cloud
- Analyzing sentiment
- Extracting emotions from text
- Clustering similar entities based on text
- Using classification for supervised learning
- Recommending items to users based on text data analytics