This project was completed as part of the Miuul - Linear Algebra for Data Science and Machine Learning course. The objective of the project was to apply the linear algebra concepts covered in the ...

This project covers a few linear algebra concepts. We first evaluate a classification model using the k-nearest neighbor algorithm. The prediction model is trained using the original data as well as ...

Core math topics like linear algebra, statistics, and calculus form the foundation of data science.• Real-world projects and ...

Python for Linear Algebra. These pages provide a showcase of how to use Python to do computations from linear algebra. We will demonstrate both the NumPy (SciPy) ... i.e. floating point numerical data ...

Figure 1. Goals of compressed linear algebra. Adapted column-oriented compression schemes for numeric matrices, and cache-conscious linear algebra operations over these compressed matrices (Section 3) ...

Machines or computers only understand numbers. And these numbers need to be represented and processed in a way that lets machines solve problems by learning from the data instead of learning from ...

Linear algebra is sub field of mathematics and contains matrix's, Operations on dataset, Vectors. Linear algebra is core base for purely statistics and mathematics person to achieve goals with basic ...

Specialization: Statistical Modeling for Data Science ApplicationsInstructor: Brian Zaharatos, Director, Professional Master’s Degree in Applied MathematicsPrior knowledge needed: Differentiation, ...