Beginner - Expert Linear Algebra, with Practice in Python.
- Description
- Curriculum
- FAQ
- Reviews
In this course, we look at core Linear Algebra concepts and how it can be used in solving real world problems. We shall go through core Linear Algebra topics like Matrices, Vectors and Vector Spaces. If you are interested in learning the mathematical concepts in linear algebra, but also want to apply those concepts to datascience, statistics, finance, engineering, etc.then this course is for you! We shall explain detaily all Maths Concepts and also implement them programmaticaly in Python. We lay much emphasis on feedback. Feel free to ask as many questions as possible!!! Let’s make this course as interactive as possible, so that we still gain that classroom experience.
Here are the different concepts you’ll master after completing this course.
- Fundamentals of Linear Algebra
- Operations on a single Matrix
- Operations on two or more Matrices
- Performing Elementary row operations
- Finding Matrix Inverse
- Gaussian Elimination Method
- Vectors and Vector Spaces
- Fundamental Subspaces
- Matrix Decompositions
- Matrix Determinant and the trace operator
- Core Linear Algebra concepts used in Machine Learning and Datascience
- Hands on experience with applying Linear Algebra concepts using the computer with the Python Programming Language
- Apply Linear Algebra in real world problems
- Skills needed to pass any Linear Algebra exam
- Principal Component Analysis
- Linear Regression
YOU’LL ALSO GET:
- Lifetime access to This Course
- Friendly and Prompt support in the Q&A section
- Udemy Certificate of Completion available for download
- 30-day money back guarantee
Who this course is for:
- Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.
- Anyone who wants to master deep learning fundamentals and also practice deep learning using best practices in TensorFlow.
- Deep Learning Practitioners who want gain a mastery of how things work under the hood.
- Beginner Python Developers curious about Deep Learning.
Enjoy!!!
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5Matrix Definition 1Video lesson
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6Matrix Definition 2Video lesson
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7Matrix AdditionVideo lesson
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8Matrix Multiplication 1Video lesson
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9Matrix Multiplication 2Video lesson
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10Matrix PropertiesVideo lesson
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11Matrix TransposeVideo lesson
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12Matrix Inverse - IntroductionVideo lesson
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13Matrix Inverse - Echelon RulesVideo lesson
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14Matrix Inverse - RREFVideo lesson
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15Matrix Inverse - GAUSSVideo lesson
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16Matrix Inverse - ComputationVideo lesson
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17Practical SessionVideo lesson
Practice
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31DefinitionVideo lesson
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32SubspacesVideo lesson
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33Linear CombinationVideo lesson
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34SpanVideo lesson
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35Generated SubspaceVideo lesson
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36Linear IndependenceVideo lesson
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37Fundamental Subspaces - Nul SpaceVideo lesson
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38Fundamental Subspaces - Column SpaceVideo lesson
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39BasisVideo lesson
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40Coordinate Systems and Change of BasisVideo lesson
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41Dimension and RankVideo lesson
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42Practical SessionVideo lesson
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58DefinitionVideo lesson
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59Eigen DecompositionVideo lesson
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60DiagonalizationVideo lesson
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61Cholesky DecompositionVideo lesson
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62Singular Value DecompositionVideo lesson
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63Full rank approximationVideo lesson
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64Low Rank ApproximationVideo lesson
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65Fundamental subspacesVideo lesson
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66Practical SessionVideo lesson

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