From 3fc8e5d94a984a8545aff8d196c44baf2b1009c3 Mon Sep 17 00:00:00 2001 From: Diego Javier Zea Date: Wed, 28 Feb 2024 09:51:15 +0100 Subject: [PATCH] Fix https://github.com/FluxML/Flux.jl/issues/2380 --- docs/src/tutorials/logistic_regression.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/tutorials/logistic_regression.md b/docs/src/tutorials/logistic_regression.md index 858e907cd5..b6775e9f89 100644 --- a/docs/src/tutorials/logistic_regression.md +++ b/docs/src/tutorials/logistic_regression.md @@ -35,7 +35,7 @@ julia> x |> summary The `y` values here corresponds to a type of iris plant, with a total of 150 data points. The `x` values depict the sepal length, sepal width, petal length, and petal width (all in `cm`) of 150 iris plant (hence the matrix size `4×150`). Different type of iris plants have different lengths and widths of sepals and petals associated with them, and there is a definitive pattern for this in nature. We can leverage this to train a simple classifier that outputs the type of iris plant using the length and width of sepals and petals as inputs. -Our next step would be to convert this data into a form that can be fed to a machine learning model. The `x` values are arranged in a matrix and should ideally be converted to `Float32` type (see [Performance tips](@ref man-performance-tips)), but the labels must be one hot encoded. [Here](https://discourse.julialang.org/t/all-the-ways-to-do-one-hot-encoding/64807) is a great discourse thread on different techniques that can be used to one hot encode data with or without using any external Julia package. +Our next step would be to convert this data into a form that can be fed to a machine learning model. The `x` values are arranged in a matrix and should ideally be converted to `Float32` type (see [Performance tips](@ref id-man-performance-tips)), but the labels must be one hot encoded. [Here](https://discourse.julialang.org/t/all-the-ways-to-do-one-hot-encoding/64807) is a great discourse thread on different techniques that can be used to one hot encode data with or without using any external Julia package. ```jldoctest logistic_regression julia> x = Float32.(x);