Course Content
Data Preprocessing
Data Preprocessing
Challenge
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users
Everything was clear?
Challenge
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users
Everything was clear?
Challenge
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users
Everything was clear?
Task
Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.
- Create a new feature
Age Binning
(like before) that bins the users' ages into age groups (e.g. 20-30, 30-40, 40-50, etc.). Like, 35 (int) -> 30-40 (str) - Create a second feature
Average Hours
that counts the average number of hours per week spent on social media by individual users