Linear Algebra for Data Science in Python

Description

Get started with using linear algebra in your data science projects

Vectorizing your code is an essential skill to make your calculations faster and take advantage of the capabilities of modern machine and deep learning packages. This course will get you up and running with linear algebra fundamentals for data science in Python. In this course, you will learn about scalars, vectors, and matrices and the geometrical meaning of these objects. You will also learn how you should use linear algebra in your Python code. In addition to this, you'll be able to perform operations such as addition, subtraction and dot product. As you cover further sections, you'll focus on the different syntactical errors you can encounter while vectorizing your code. By the end of this course, you will have gained the skills you need to use linear algebra confidently in your data science projects. All code and supporting files for this course are available at - https://github.com/PacktPublishing/Linear-Algebra-for-Data-Science-in-Python

Focus on the addition and subtraction of Matrix
Understand errors when adding matrices
Learn why linear algebra is useful

This course is designed for aspiring data scientists or anyone who wants to learn linear algebra in Python.

This course takes you through linear algebra in a systematic manner. It is even packed with step-by-step instructions and working examples to enhance your learning experience.

Learn linear algebra for data science and understand the essential concepts * Understand matrix, scalars, and vectors and learn how to use them

https://github.com/packtpublishing/linear-algebra-for-data-science-in-python

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1. Linear Algebra Fundamentals