Python NumPy: Scientific Computing with Python
Stone River eLearning
Summary
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Overview
At the end of this course, you will have a thorough understanding of Numpy' s features and when to use them. Numpy is mainly used in matrix computing. We'll do a number of examples specific to matrix computing, which will allow you to see the various scenarios in which Numpy is helpful. There are a few computational computing libraries available for Python. It's important to know when to choose one over the other. Through rigorous exercises, you'll experience where Numpy is powerful and develop and understanding of the scenarios in which Numpy is most useful.
- Express fully why Numpy should be used
- Ability to install Numpy
- Understanding of how to use Numpy
What Will I Learn?
- Express fully why Numpy should be used
- Ability to install Numpy
- Understanding of how to use Numpy
Description
Class Curriculum
NumPy
Start
Introduction (1:13)
Preview
What is Numpy (3:12)
Start
Basic Mathematics (6:23)
Start
Tour of Numpy I (8:02)
Start
Tour of Numpy II (10:17)
Start
Matrices (6:56)
Preview
Deviations (3:18)
Start
Eigen Values (5:18)
Start
Covariance (9:55)
Start
Project (Determinants) (9:33)
Start
Summary (1:03)
Who is this course for?
- Those wanting to know about Python libraries helpful for computational computing
Requirements
- Some Python experience
- Some experience working with matrices will be helpful
Career path
Web developer
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