Introduction:

Linear algebra is a field of mathematics that is universally agreed to be a prerequisite to a deeper understanding of machine learning. Although linear algebra is a large field with many esoteric theories and findings, the nuts and bolts tools and notations taken from the field are practical for machine learning practitioners. With a solid foundation of what linear algebra is, it is possible to focus on just the good or relevant parts.

Course Description:
In DIU, this course is known as Mathematics II. It consists of 2 different mathematical courses viz Linear Algebra (80% of Math-II) & Coordinate Geometry (20% of Math-II).
Course synopsis:
Linear Algebra deals with matrices & linear transformations in detail. Coordinate Geometry deals with (i) different
coordinate systems & (ii) mutual relationships between algebraic equations & geometric structures.
Course Outcomes:
It is offered as the most important mathematical course for TE students throughout all universities of the world. It helps them to become experts at (i) making programming languages, (ii) networking, (iii) robotics, (iv) developing webs, (v) computer graphics, and many other discourses.
Learning Approaches:
The whole curriculum content is broken down into small units so that they can be easily mastered. The teacher will make sure that all students have mastered a unit taught before proceeding to the next unit. Instructors remain concerned about the expected learning outcome of each unit and so take an assessment at the end of each unit to determine whether the learning outcome is achieved. Also, we bring out enrichment or remedial activities based on pupils’ achievements before proceeding to the next unit.