Learning Python for Numeric and Scientific Applications

My purpose in learning Python is mainly for numeric and scientific applications, such as AI deep learning.  So my notes will focus mainly on using Python for these types of applications.

The code below demonstrates a little about Python such as some variables and types; lists; subsetting and slicing lists; adding, removing and copying lists; some of its built-in functions and built-in object methods.  Then it demonstrates how to use the NumPy package specifically the NumPy array, some NumPy statistical methods, and how to generate your own sample data.  You can run this code online and I recommend using repl.it.

 

Additional References:

• Python.org
• Numeric and Scientific Python Modules, Libraries, Tools, and Frameworks
• The Python Standard Library
• Installing Python Modules
• NumPy
• Top 5 Python IDEs For Data Science
• Jupyter
• Spyder - Documentation