Question

What are some scenarios in which you are likely to encounter a sparse matrix?

Answer 1

Sparse matrices turn up a lot in applied machine learning.

Data

Sparse matrices come up in some specific types of data, most notably observations that record the occurrence or count of an activity.

Three examples include:

• Whether or not a user has watched a movie in a movie catalog.
• Whether or not a user has purchased a product in a product catalog.
• Count of the number of listens of a song in a song catalog.

Data Preparation

Sparse matrices come up in encoding schemes used in the preparation of data.

Three common examples include:

• One-hot encoding, used to represent categorical data as sparse binary vectors.
• Count encoding, used to represent the frequency of words in a vocabulary for a document
• TF-IDF encoding, used to represent normalized word frequency scores in a vocabulary.

Areas of Study

Some areas of study within machine learning must develop specialized methods to address sparsity directly as the input data is almost always sparse.

Three examples include:

• Natural language processing for working with documents of text.
• Recommender systems for working with product usage within a catalog.
• Computer vision when working with images that contain lots of black pixels.