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Posts with the tag math:

Linear Regression with Go

Linear regression is a common statistical data analysis technique.

It is used to determine the extent to which there is a linear relationship between a dependent variable and one or more independent variables, and is widely used in machine learning applications.

There are two types of linear regression, simple linear regression and multiple linear regression.

In simple linear regression a single independent variable is used to predict the value of a dependent variable. In multiple linear regression two or more independent variables are used to predict the value of a dependent variable. The difference between the two is the number of independent variables. In both cases there is only a single dependent variable.

In this post I’m going to introduce basic concepts on linear regression and build a simple linear regression example using go and spago.

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Partial Derivatives & Recursive Descent

Writing partial derivatives is a great way to understand some of the underlying features of machine learning and neural network libraries.

In this post I’ll explain how partial derivates are a necessary building block in understanding machine learning and neural networks, and how to write some python code to help bring partial derivates and recursive descent to life!

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