Now you've seen some of what NumPy can do, it's time to practice your skills!
In this assignment, you'll work through a Jupyter Notebook full of exercises based on what we've covered in the NumPy section videos.
Download the NumPy exercises and solutions notebooks from GitHub and work through each cell in the exercises notebook using what you've learned in the previous videos.
NumPy Exercises Solutions notebook (avoid looking at this for as long as possible)
Don't forget, if you get stuck, there's plenty of help available!
Remember, you should always try to run the code yourself first.
If you're still stuck feel free to ask the Discord server (Checkout the #machinelearning-datascience channel for help) or search the internet for answers.
Note: In the notebook, there may be instructions to import a file from a file path such as "../data/car-sales.csv", you should change these to wherever you're storing "car-sales.csv". Or the direct link on GitHub (in raw format), such as, https://raw.githubusercontent.com/mrdbourke/zero-to-mastery-ml/master/data/car-sales.csv.
After working through the NumPy exercises notebook, how did you go?
If you made through, congratulations! If you struggled along the way, don't worry, it would be surprising if you were able to retain everything which was covered in the lectures.
The best way to improve your NumPy skills is to keep practising.
Keep in mind some of the things you've learned about NumPy for whenever you need to manipulate numerical data with Python.