NumPy Essential Training: 2 MatPlotlib and Linear Algebra Capabilities
1h 13mIntermediate2022-03-04
Authors

Terezija Semenski
Software Developer, Mathematician, Writer, and Learner
Course details
NumPy provides the numerical backend for nearly every scientific or technical library for Python. Many advanced data science and machine learning libraries require data to be in the form of NumPy arrays before it can be processed. In this course, instructor Terezija Semenski gives you a closer look at advanced features in NumPy and Matplotlib. Matplotlib is the most popular library for plotting with NumPy. Terezija steps you through the basics of plotting functions and implementing figures with Matplotlib, then goes over advanced commands and plots. She introduces universal functions in NumPy, as well as strides, structure arrays, dates, and times. Terezija also covers basic linear algebra capabilities that you can apply in NumPy, including decomposition, polynomial mathematics, and linear regression.
Skills covered
NumPyData VisualizationMachine LearningData AnalysisEssential TrainingArtificial Intelligence (AI)Data ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen Source
Concepts
0. Introduction
- 01 - Introduction
- 02 - What you should know
1. Plotting with Matplotlib
- 03 - Why should you use Matplotlib
- 04 - Matplotlib basics
- 05 - Understanding figures
- 06 - Matplotlib subplots functionality
- 07 - Understanding legends
- 08 - Challenge - Implementing a figure
- 09 - Solution - Implementing a figure
2. Matplotlib Styling and Advanced Plots
- 10 - Colors and styles
- 11 - Advanced Matplotlib commands
- 12 - Adding annotations
- 13 - Creating pie charts and bar charts
- 14 - Advanced plots
3. From Beginner to Advanced NumPy
- 15 - Universal functions
- 16 - Introducing strides
- 17 - Structured arrays
- 18 - Dates and time in NumPy
4. Linear Algebra in NumPy
- 19 - Linear algebra capabilities in NumPy
- 20 - Decomposition
- 21 - Polynomial mathematics
- 22 - Application - Linear regression
Conclusion
- 23 - Next steps
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