ARTICLEOne-Hot Encoding For Categorical Data
Star
Covers: theory of Tabular Data Preprocessing
Estimated time needed to finish: 12 minutes
Questions this item addresses:
  • What is one-hot encoding?
  • How do we work with discrete, categorical data?
How to use this item?

Read the whole article.

URL: https://towardsdatascience.com/understanding-feature-engineering-part-2-categorical-data-f54324193e63
Author(s) / creator(s) / reference(s)
Dipanjan Sarkar
0 comment
Recipe
publicShare
Star0

Tabular Data Preprocessing for Categorical Data

Contributors
Total time needed: ~38 minutes
Objectives
You will learn three methods to preprocess categorical tabular data.
Potential Use Cases
Time-series forecasting, anomaly detection, power generation
Who is This For ?
BEGINNERData Scientists new to Tabular Data/Time-Series Preprocessing.
Click on each of the following annotated items to see details.
ARTICLE 1. One-Hot Encoding For Categorical Data
  • What is one-hot encoding?
  • How do we work with discrete, categorical data?
12 minutes
ARTICLE 2. The Fourier Transformation
  • What is a Fourier Transformation?
10 minutes
ARTICLE 3. Understanding the Fourier Transform by Example
  • I still don't understand the Fourier Transform—can you explain it again?
5 minutes
ARTICLE 4. Embedding For Categorical Variables
  • How do you use embeddings in tabular data preprocessing?
5 minutes
LIVE_SESSION 5. AISC Tabular Data Preprocessing Presentation
  • Can you summarize this recipe?
6 minutes

Concepts Covered

0 comment