Vector Space in Data Science
Understand how vector spaces form the foundation for representing data points and parameters in data science. Learn how feature vectors correspond to real-world data like images and how parameter spaces influence model training, especially within linear regression and machine learning pipelines.
From abstract to real vector space
All data (text, images, videos, sound) is made up of data points or samples, which can be represented as column vectors having real numbers. That said, we already know that all d-dimensional vectors compose the vector space over the field . So, we can say that is the most popular vector space used in data science because all data is represented using vectors that span . Here, represents the dimension of the vector space, ...