Maths for Data Science by DataTrained
Requirements
10th class Level math knowledge is expected
Description
Overview: Explore the application of key mathematical topics related to linear algebra with the Python programming language.
Expected Duration: After completion of this course, you should be able to accomplish the objectives from the following lessons and topics.
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Lessons on Math for Data Science & Machine Learning:
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Understand how to work with vectors in Python
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Basis and Projection of Vectors: Understand the Basis and Projection of Vectors in Python
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Work with Matrices: Understand how to work with matrices in Python
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Matrix Multiplication: Understand how to multiply matrices in Python
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Matrix Division: Understand how to divide matrices in Python
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Linear Transformations: Understand how to work with linear transformations in Python
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Gaussian Elimination: Understand how to apply Gaussian Elimination
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Determinants: Understand how to work with determinants in Python
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Orthogonal Matrices: Understand how to work with orthogonal matrices in Python
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Eigenvalues: Recognize how to obtain eigenvalues from eight decompositions in Python
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Eigenvectors: Recognize how to obtain eigenvectors from eigendecomposition in Python
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PseudoInverse: Recognize how to obtain pseudoinverse in Python
Who this course is for:
Beginner python developers looking for a data science career
https://www.udemy.com/course/maths-for-data-science-by-datatrained/