Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.Apprendre Challenge | Feature Engineering
Data Preprocessing
course content

Contenu du cours

Data Preprocessing

Data Preprocessing

1. Brief Introduction
Data TypesData Processing MethodsDataset: Test and TrainingDeleting an "Extra" DataChanging the Data Type
2. Processing Quantitative Data
Data ScalingData Scaling vs Data NormalizationRemoving OutliersRemoving Missing ValuesData Augmentation: Synthetic Data
3. Processing Categorical Data
Methods for Encoding the Categorical DataOne-Hot EncodingOrdinal EncodingLabel Encoding of the Target VariableChallenge
4. Time Series Data Processing
Data Type ConversionData CleaningStationarityDenoisingTrain/Test Split & Cross ValidationChallenge
5. Feature Engineering
Technique IdeaRealizationFeature Extraction from TextFeature Extraction from ImagesFeature Extraction from Time SeriesChallenge
6. Moving on to Tasks
Challenge 1Challenge 2Challenge 3

book
Challenge

Tâche

Swipe to start coding

Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.

  1. 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)
  2. Create a second feature Average Hours that counts the average number of hours per week spent on social media by individual users

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 5. Chapitre 6
toggle bottom row

book
Challenge

Tâche

Swipe to start coding

Now you can solve a fairly simple task - read a synthetic dataset with profiles on a social network and create new features.

  1. 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)
  2. Create a second feature Average Hours that counts the average number of hours per week spent on social media by individual users

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 5. Chapitre 6
Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
We're sorry to hear that something went wrong. What happened?
some-alt