day2.md

Introduction to the Concept of Machine Learning

Objectives

• Greetings/Announcements

• Students work on training their machine - they will present these at the end of class and upload them to canvas - Must have 1 class per student

  • Groups of 2-3

• 15 minute break

• Check in on Student Status

• Students Present their Teachable Machines

  • Discuss how to submit assignment

• 15 minute break

• Discussion about projects and what was learned (15-20 mins)

• Do findings on Jamboard

• Introduction to R Syntax and Output

    5+7
    x <- 2  # Defining variable (variables are case sensitive)
    x <- 3  

    x # outputs value stored by x

    y <- c(1,2,3,4,5) # c is the concatenation operator
    y <- 1:10         # creates a vector with 10 values from 1 to 10
    x <- y <- 1:10    # x and y equal to same thing

    z <- x+y          # adds together the items at each index

    z2 <- x-y     # subtracts together the items at each index

    ls()    #outputs all values in workspace

    rm(x)     #clears the x var from the workspace

    rm(list = ls)   #clears all variables


    browseURL("http://www.google.com")  #Opens up browser and goes to Url


    library() #gives list of all packages installed
    search() #list of packages currently installed and usable

• Students pair program R assignment 1
• Review assignment Solution
• Start Team Assigment 2 - R assignment 2

References

• Machine Learning Explained in 100 Seconds