Python NumPy: Scientific computing with Python
What you'll learn
- Express fully why Numpy should be used
- Ability to install Numpy
- Understanding of how to use Numpy
Course content
- Preview01:13
- 03:12What is Numpy
- 06:23Basic Mathematics
- 08:02Tour of Numpy I
- 10:17Tour of Numpy II
- Preview06:56
- 03:18Deviations
- 05:18Eigen Values
- Preview09:55
- 09:33Project (Determinants)
- 01:03Module Summary
Requirements
- Some Python experience
- Some experience working with matrices will be helpful
Description
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
Who this course is for:
- Those wanting to know about Python libraries helpful for computational computing
Instructor
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