Math and Architectures of Deep Learning

4 Linear algebraic tools in machine learning

This chapter covers

• Quadratic forms
• Applying principal component analysis (PCA) in data science
• Retrieving documents with a machine learning application

Finding patterns in large volumes of high-dimensional data is the name of the game in machine learning and data science. Data often appears in the form of large matrices (a toy example of this is shown in section 2.3 and also in equation 2.1). The rows of the data matrix represent feature vectors for individual input instances. Hence, the number of rows matches the count of observed input instances, and the number of columns matches the size of the feature vector—that is, the number of dimensions in the feature space. Geometrically speaking, each ...