Linear Algebra for Data Science in Python

Linear Algebra for Data Science in Python
Linear Algebra for Data Science in Python
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 0h 56m | 342 MB

Know all about Linear Algebra for Data Science in Python

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.

Learn

  • Learn about Matrix
  • Scalars and Vectors
  • Addition and Subtraction of Matrix
  • Errors when Adding Matrices
  • Why is Linear Algebra Useful?
Table of Contents

Linear Algebra
1 What is matrix
2 Scalars and vectors
3 Linear algebra and geometry
4 Arrays in Python
5 What is a tensor
6 Adding and subtracting matrices
7 Errors when adding matrices
8 Transpose
9 Dot product of vectors
10 Dot product of matrices
11 Why are matrices useful