# Accelerating linear methods

**URL:** https://discourse.julialang.org/t/accelerating-linear-methods/99685
**Category:** Machine Learning
**Tags:** question
**Created:** [May 31, 2023, 7:14pm UTC](https://discourse.julialang.org/t/accelerating-linear-methods/99685 "2023-05-31T19:14:06Z")
**Posts on this page:** 1
**Showing post:** 9

<div class="post-metadata">

### Author: ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)
#### Post date: [June 1, 2023, 5:38am UTC](https://discourse.julialang.org/t/accelerating-linear-methods/99685/9 "2023-06-01T05:38:11Z")

</div>

This discussion was had before, much of it is likely unchanged:

> [@Efficient way of doing linear regression](https://discourse.julialang.org/t/efficient-way-of-doing-linear-regression/31232):
>
> Hello, I need an efficient way to performs linear regression because I have to fit several segments in a big for loops which takes time to achieve. In the past, their was a linreg function which has been depreciated. Currently I am using polyfit to do a polynomial fit of order 1, for each segment. Is there a more efficient way to do this ?

I agree with Peter, if you are fitting models with high dimensional fixed effects look at FixedEffectModels which is designed for this and also has GPU support.

---

_[View the full topic](https://discourse.julialang.org/t/accelerating-linear-methods/99685)._