NumPy provides the numerical backend for nearly every scientific or technical library for Python. Many advanced data science and machine learning libraries require data to be in the form of NumPy arrays before it can be processed. In this course, instructor Terezija Semenski gives you a closer look at advanced features in NumPy and Matplotlib. Matplotlib is the most popular library for plotting with NumPy. Terezija steps you through the basics of plotting functions and implementing figures with Matplotlib, then goes over advanced commands and plots. She introduces universal functions in NumPy, as well as strides, structure arrays, dates, and times. Terezija also covers basic linear algebra capabilities that you can apply in NumPy, including decomposition, polynomial mathematics, and linear regression.
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