This course is part of the Mathematics for Machine Learning and Data Science Specialization by DeepLearning.AI. After completing this course, learners will be able to: Represent data as vectors and ...

Vector a is [1, 2, 3, 4]. Vector b is [5, 6, 7, 8]. Vectors have various vector-y functions that work how you'd expect. The sum of a and b is [6, 8, 10, 12]. The dot ...

NumPy includes some tools for working with linear algebra in the numpy.linalg module. However, unless you really don’t want to add SciPy as a dependency to your project, it’s typically better to use ...

This course aims to develop your knowledge in the mathematics topics of linear algebra and calculus, which provides the basic mathematics foundation that is necessary for anyone pursuing a computing ...

The * means the namespace for all functions in SymPy are loaded, so we can call them directly without having to preface them with the package name. Vectors and Matrices are created as instances of a ...

TODD, J. (1) Determinants and Matrices (2) Theory of Equations (3) Integration (4) Vector Methods: Applied to Differential Geometry, Mechanics and Potential Theory (5) Integration of Ordinary ...

The Clifford algebra is a unification and generalization of real number, complex number, quaternion, and vector algebra, which accurately and faithfully characterizes the intrinsic properties of space ...

Abstract: Vector logic is a matrix–vector representation of the logical calculus inspired in neural network models. In this algebraic formalism, the truth values map on orthonormal Q-dimensional ...