1) Binary classification There are two types of supervised learning—classification and regression. Binary classification is used to predict a target variable that has only two labels, typically represented numerically with a zero or a one. The .head() of a dataset, churn_df, is shown…
1) Descriptive and inferential statistics Statistics can be used to answer lots of different types of questions, but being able to identify which type of statistics is needed is essential to drawing accurate conclusions. In this exercise, you’ll sharpen your…
1)The long and the wide As part of a data scientist job interview, you need to answer some technical questions. One of the challenges is to show the differences between long and wide data formats. In this exercise, you will…
1)Inspecting a DataFrame When you get a new DataFrame to work with, the first thing you need to do is explore it and see what it contains. There are several useful methods and attributes for this. homelessness is a DataFrame containing…
1)What column to merge on? Chicago provides a list of taxicab owners and vehicles licensed to operate within the city, for public safety. Your goal is to merge two tables together. One table is called taxi_owners, with info about the taxi…
1)What does time.time() measure? What does the time.time() function exactly measure? 2)Measuring time I In the lecture slides, you saw how the time.time() function can be loaded and used to assess the time required to perform a basic mathematical operation. Now, you will use…
1)Examining the dataset Throughout this course, you’ll be analyzing a dataset of traffic stops in Rhode Island that was collected by the Stanford Open Policing Project. Before beginning your analysis, it’s important that you familiarize yourself with the dataset. In this…
