From 2c9cdd1277257a274cf6ddf5bab80ae97706d59a Mon Sep 17 00:00:00 2001 From: Saransh Date: Tue, 23 Aug 2022 20:31:43 +0530 Subject: [PATCH] Better introduction to a ML pipeline --- docs/src/getting_started/linear_regression.md | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/docs/src/getting_started/linear_regression.md b/docs/src/getting_started/linear_regression.md index 58f90914c0..6859c9f136 100644 --- a/docs/src/getting_started/linear_regression.md +++ b/docs/src/getting_started/linear_regression.md @@ -1,5 +1,14 @@ # Linear Regression +Flux is a pure Julia ML stack that allows you to build predictive models. Here are the steps for a typical Flux program: + +- Provide training and test data +- Build a model with configurable parameters to make predictions +- Iteratively train the model by tweaking the parameters to improve predictions +- Verify your model + +Under the hood, Flux uses a technique called automatic differentiation to take gradients that help improve predictions. Flux is also fully written in Julia so you can easily replace any layer of Flux with your own code to improve your understanding or satisfy special requirements. + The following page contains a step-by-step walkthrough of the linear regression algorithm in `Julia` using `Flux`! We will start by creating a simple linear regression model for dummy data and then move on to a real dataset. The first part would involve writing some parts of the model on our own, which will later be replaced by `Flux`. ## A simple linear regression model