Packt – Linear Algebra for Data Science in Python-XQZT
English | Size: 338.84 MB
Learn about Matrix
Scalars and Vectors
Addition and Subtraction of Matrix
Errors when Adding Matrices
Why is Linear Algebra Useful?
This is a straightforward course to learn Linear Algebra Fundamentals for Data Science in Python. Vectorizing your code is an essential skill to make your calculations faster and take advantage of the full capabilities of modern machine and deep learning packages. In this course, you will learn about scalars, vectors, and matrices. You will see how and why to use linear algebra in your Python code and the geometrical meaning of these objects. Addition, subtraction and dot product are only some of the operations you will be able to perform. We will also look into the different syntactical errors you can encounter while vectorizing your code to make sure you have acquired the skills to use linear algebra in your data science projects.
All the codes and supporting files for this course are available at: https://github.com/PacktPublishing/Linear-Algebra-for-Data-Science-in-Python
Learn Linear Algebra for Data Science and understand the concepts
Understand Matrix, Scalars, and Vectors and learn how to use it
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