No Data Science course can be complete without learning NumPy (Numerical Python). NumPy is a Python library thats used in almost every field of science and engineering. Its practically THE standard for working with numerical data in Python. The case studies for how NumPy is being used speak for themselves  

So far, weve been using Pandas, which is built on top of NumPy. Think of Pandas as a high-level data manipulation tool that includes functionality for working with time-series or for grouping, joining, merging and finding missing data (i.e., everything weve been doing so far). NumPy on the other hand shines with low-level tasks, like doing serious math and calculations.

Today you'll learn:

• How to leverage the power of NumPy's ndarrays.

• How to access individual values and subsets inside an n-dimensional array.

• How broadcasting works with ndarrays.

• How to do linear algebra with NumPy.

• How to generate points that you can plot on a chart.

• How to manipulate images as ndarrays.
  

Download and add the Notebook to Google Drive

As usual, download the .zip file from this lesson and extract it. Add the .ipynb file into your Google Drive and open it as a Google Colaboratory notebook.

Add the Data to the Notebook

The .zip file also includes an image. This is the data for the project. Add this file to your notebook.