Numpy Python Tutorial | Numpy Indexing and Slicing | Numpy Broadcasting

In this video, you’ll learn about how to perform indexing, slicing and broadcasting using the Numpy Python Library. This library is essential to Machine Learning as it allows you to efficiently work with data through arrays and matrices! You’ll learn how to perform selection of an array through square brackets, how to utilize Slicing to obtain specific values of your array, how to perform indexing and selection on both 1D arrays and 2D arrays, how to broadcast a value to the entire array as well as specific portions, how to create a copy of an array, and how to relate Booleans and arrays to filter your array based on specific conditions. After watching this video and learning the basics of indexing using Numpy, there’s an activity right below this description for you to try out on your own using the skills you learned here. Enjoy!

NUMPY ACTIVITY:

Create a random 2 dimensional Numpy array and change the upper right corner to display ‘hi’, while keeping the rest of the matrix the same.

TIMESTAMP:

00:00 Introduction & Recap of Last Video
00:18 Lesson Structure for Numpy Indexing Video
00:32 Indexing, Selection, and Slicing
03:13 Broadcasting
04:39 Relating Booleans and Arrays
05:18 Recap of All Content in Video
06:00 Call-to-action: Numpy Indexing

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