Зміст курсу
Data Preprocessing
Data Preprocessing
Challenge
Swipe to show code editor
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
Дякуємо за ваш відгук!
Challenge
Swipe to show code editor
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
Дякуємо за ваш відгук!
Challenge
Swipe to show code editor
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
Дякуємо за ваш відгук!
Swipe to show code editor
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