NumPy Essential Training: 1 Foundations of NumPy
1h 26mIntermediate2023-10-19
Authors
Terezija Semenski
Software Developer, Mathematician, Writer, and Learner
Course details
NumPy provides Python with an elegant syntax and powerful array processing library. NumPy is the most useful and most powerful library in Python when it comes to data science and machine learning. In this course, Terezija Semenski introduces the NumPy data structure for n-dimensional arrays, then continues by showing functions for creating and manipulating arrays, including indexing and slicing for extracting elements from arrays. She also details how to find unique elements and reverse an array, and describes functions and operators for performing computations with ndarray objects and functions for math and statistics.
Skills covered
NumPyMachine LearningPythonData AnalysisEssential TrainingArtificial Intelligence (AI)Data ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen Source
Concepts
0. Introduction
- 01 - Take advantage of the power of NumPy
- 02 - What you should know
1. NumPy Overview and Introduction to Jupyter Notebook
- 03 - Why should you use NumPy
- 04 - Python lists vs. NumPy arrays
- 05 - Jupyter Notebook basics
2. NumPy Array Types and Creating NumPy Arrays
- 06 - Array types and conversions between types
- 07 - Multidimensional arrays
- 08 - Creating arrays from lists and other Python structures
- 09 - Intrinsic NumPy array creation
- 10 - Creating arrays filled with constant values
- 11 - Finding the shape and size of an array
3. Manipulate NumPy Arrays
- 12 - Adding, removing, and sorting elements
- 13 - Copies and views
- 14 - Reshaping arrays
- 15 - Indexing and slicing
- 16 - Joining and splitting arrays
4. Functions and Operations
- 17 - Arithmetic operations and functions
- 18 - Broadcasting
- 19 - Aggregate functions
- 20 - How to get unique items and counts
- 21 - Transpose like operations
- 22 - Reversing an array
Conclusion
- 23 - Next steps