In today’s fast paced world, companies are relying heavily on the data that they have been collecting from their client base. This is of course a first step. They need to know how to transform this data and derive meaningful insights for future growth. In this course, Advanced Operations on Arrays with NumPy, you’ll gain the ability to apply complex mathematical operations on the data. First, you’ll explore the differences between Array copy and view, understand the differences between them, and learn when to use them. Next, you’ll discover NumPy’s matrix library and learn how to construct matrices, manipulate matrices, and perform basic arithmetic operations. Finally, you’ll learn how to represent systems of linear equations in the form of NumPy matrices, compute eigenvalues, and solve linear equations. When you’re finished with this course, you’ll have the skills and knowledge of performing complex mathematical operations on your data needed to build data models and derive meaningful results.
Author Name: Saravanan Dhandapani
Author Description:
I have worked in IT design, development, and architecture for over a decade for some of the top fortune 100 companies. I have designed and architected enterprise applications and developed scalable and portable software. I am a Google Certified Professional Architect. Critical areas where I have worked are architecture and design using Java, ESB, Tomcat, ReactJS, JavaScript, Linux, Oracle, SVN, GIT, and so on, and cloud technologies, including AWS and GCP.

Table of Contents

• Course Overview
  1min
• Exploring Array Copy and View in NumPy
  13mins
• Working with Matrices Using NumPy Matrix Library
  18mins
• Performing Complex Calculations Using NumPy Linear Algebra
  14mins