NumPy Data Science Essential Training

NumPy Data Science Essential Training Description

NumPy Data Science Essential Training covers everything you need to know about NumPy – a popular library dedicated to data science and machine learning with built-in smart syntax and powerful array processing.

The course goes from the group up with an introduction to the data structure for n-dimensional arrays before continuing to more complex functions that allow you to freely manipulate arrays, elements, indexes, and so on.

Here are what you will learn in this course:

• Introduction
  • Introduction
  • What you should know
• NumPy Overview and Introduction to Jupyter Notebook
  • Why should you use NumPy?
  • Python lists vs. NumPy arrays
  • Jupyter Notebook basics
• NumPy Array Types and Creating NumPy Arrays
  • Array types and conversions between types
  • Multidimensional arrays
  • Creating arrays from lists and other Python structures
  • Intrinsic NumPy array creation
  • Creating arrays filled with constant values
  • Finding the shape and size of an array
• Manipulate NumPy Arrays
  • Adding, removing, and sorting elements
  • Copies and views
  • Reshaping arrays
  • Indexing and slicing
  • Joining and splitting arrays
• Functions and Operations
  • Arithmetic operations and functions
  • Broadcasting
  • Aggregate functions
  • How to get unique items and counts
  • Transpose-like operations
  • Reversing an array
• Conclusion
  • Next steps