Srbija Posted August 24, 2022 Share #1 Posted August 24, 2022 (edited) Practical Linear Algebra Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz Language: English | Size: 7.24 GB | Duration: 66 lectures • 5h 35m For aspiring Data scientists and Core Engineers What you'll learn Gain graphical and physical understanding of Determinant (graphical perspective), Inverse (graphical perspective), Linear independence & dependence, Gain graphical and physical understanding of Simultaneous equations, Eigenvalue & Eigenvectors, Linear transformation, Vector & Tensor transformation Foundational linear algebra for data science, machine learning, computer vision. Conceptually it covers the engineering curriculum of linear algebra. Requirements No programming knowledge needed Description Linear algebra is fundamental and central to many branches of mathematics and is highly relevant to current sciences such as data science, machine learning and more. The course is fundamentally designed for aspiring core engineers and data scientists, incepting from the grass root level, and is discussed in the context of engineering. The unique feature of this course is that mathematical ideas are narrated via graphical animation. This unique feature helps provide highest clarity on mathematical ideas and builds graphical intuition. Levels of Practical Linear Algebra * Fundamentals of linear algebra * GATE Preparations * Higher Order Thinking * Building Research Aptitude Key Subject Take-aways Gain graphical and physical understanding of concepts such as * Determinant (graphical perspective) * Inverse (graphical perspective) * Linear independence & dependence * Simultaneous equations * Eigenvalue & Eigenvectors * Linear transformation * Vector transformation * Tensor transformation Practical Take-aways * Complete preparation for GATE-Mathematics. * Foundational linear algebra for data science, machine learning, computer vision. * Conceptually it covers the engineering curriculum of linear algebra. Advanced Discussions * Multiple perspectives to circle to ellipse transformation. * Detailed understanding of Eigen decomposition. * Coordinate transformation of engineering tensors. HOT and Research Aptitude HOT and research aptitude sections emphasise on vector and tensor transformation which is fundamental to computer graphics. The idea of transformation is relevant to even computer vision. We recommend this course to young engineers who really want to apply linear algebra to engineering situation Who this course is for Undergraduates and those preparing for competitive exams Those who want to take up assignments in machine learning /data science. Math enthusiasts Math faculties who want to innovate and teach with engineering relevance. Homepage Hidden Content Give reaction to this post to see the hidden content. Download from RapidGator Hidden Content Give reaction to this post to see the hidden content. Download from Keep2Share Edited December 26, 2022 by Bad Karma Dead links removed Link to comment
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