Description
Welcome! That is Deep Learning, Machine Learning, and Data Science Conditions: The Numpy Stack in Python.
One query or concern I get lots is that folks need to study deep studying and information science, in order that they take these programs, however they get left behind as a result of they don’t know sufficient concerning the Numpy stack in order to show these ideas into code.
Even when I write the code in full, should you don’t know Numpy, then it’s nonetheless very laborious to learn.
This course is designed to take away that impediment – to point out you do issues in the Numpy stack which are incessantly wanted in deep studying and information science.
So what are these issues?
Numpy. This kinds the idea for every thing else. The central object in Numpy is the Numpy array, on which you are able to do numerous operations.
The bottom line is {that a} Numpy array isn’t only a common array you’d see in a language like Java or C++, however as a substitute is sort of a mathematical object like a vector or a matrix.
Meaning you are able to do vector and matrix operations like addition, subtraction, and multiplication.
Crucial facet of Numpy arrays is that they’re optimized for pace. So we’re going to do a demo the place I show to you that utilizing a Numpy vectorized operation is quicker than utilizing a Python record.
Then we’ll take a look at some extra sophisticated matrix operations, like merchandise, inverses, determinants, and fixing linear methods.
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