Akuna Capital Quantitative Researcher Intern Interview Question
Dimensionality reduction is a crucial concept in the field of quantitative research, data analysis, and machine learning. For roles like Quantitative Researcher Intern at Akuna Capital, a strong understanding of dimensionality reduction techniques can help you excel in interviews and in real-world problem solving. In this comprehensive article, we will explore the most important dimensionality reduction techniques, their mathematical foundations, and practical applications, all tailored to help you ace the Akuna Capital Quantitative Researcher Intern interview.
Dimensionality reduction refers to the process of reducing the number of random variables under consideration by obtaining a set of principal variables. It is a key step in preprocessing high-dimensional data for analysis and modeling, especially in quantitative finance and data science roles at firms like Akuna Capital.
Dimensionality reduction techniques can be broadly classified into two categories:
