Lecture 2: Introduction to R Programming

In this lecture, we provide you a genital introduction to R programming. It covers the following things:

• R language, an overview
• A powerful weapon, Rstudio
• Love at first sight?
• Data type and structure in R
• Flow control
• About probability
• Other useful things

Lecture notes:

• Introduction to R programming:

  • Read the integrated notes: here;
  • Read the paginated notes: here;
  • Download the PDF notes: here.

Reading Guidelines of textbook:

For Lecture 2, it is recommended that you read the following sections in the textbook.

• Chapter 2: Read sections 2.3, pages 42 - 51.

Prepare before the Q&A session

• Read and study the materials of lecture 1 and 2 as much as you can.

• You may have some questions, and you’re welcome to ask me. If you prefer, you can also email me or send a message via Canvas to inquire.

• Think about the following questions：

  1. Imagine an idea for a machine learning project in your field. If you’re having trouble coming up with one, you can revisit our discussion in the philosophy of machine learning section.
  2. If you don’t have a good idea for question 1, learn about a potential machine learning project idea.
  3. Based on your answers to questions 1 or 2, think about what your target variable is, what potential feature variables you have, and whether your problem is a regression problem or a classification problem.
  4. Consider if you have any questions about Lectures 1 and 2.

Discussion

Slides for discussion: here

Lab exercises:

Laboratory Entrance

Solutions

Lab Queue Entrance

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