---
title: "Loss Function of 16 ML Algos"
url: https://daily.dev/posts/loss-function-of-16-ml-algos-brmfjxmh7
source_url: https://www.blog.dailydoseofds.com/p/loss-function-of-16-ml-algos
type: article
source: "Daily Dose of Data Science | Avi Chawla | Substack"
published: 2024-04-01T18:32:50.478Z
updated: 2024-04-01T18:32:49.942Z
tags: ["linear-regression", "logistic-regression", "decision-tree"]
reading_time: 3
upvotes: 2
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Loss Function of 16 ML Algos

**[Daily Dose of Data Science \| Avi Chawla \| Substack](https://daily.dev/sources/dailydoseofds)** · 3 min read · 2 upvotes · 0 comments

## Summary

An algorithm-wise summary of loss functions used in various ML algorithms.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.blog.dailydoseofds.com/p/loss-function-of-16-ml-algos>

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---

Tags: [#linear-regression](https://daily.dev/tags/linear-regression), [#logistic-regression](https://daily.dev/tags/logistic-regression), [#decision-tree](https://daily.dev/tags/decision-tree)

[View this post on daily.dev](https://daily.dev/posts/loss-function-of-16-ml-algos-brmfjxmh7)