There are so many machine learning algorithms for all machine learning problems like classification, regression, and clustering. You may be familiar with more than 3-4 algorithms for each task, but the problem every newbie faces is how to select a machine learning algorithm for the particular problem you are working on. So, in this article, I will take you through how to select a machine learning algorithm.

## How to Select a Machine Learning Algorithm?

Every newbie to machine learning faces challenges in selecting the best machine learning algorithm for the task they are working on. It’s not a big deal if you don’t know how to select an algorithm while working on a new kind of problem. As a beginner, what you can do is that whenever you come across a new problem, try to solve it using all the algorithms that can be used for that problem.

Let’s say you are working on the problem of forecasting the stock prices, this is the task of the regression because here we are predicting values that we have never seen before. So while working on such a task you can use all the regression algorithms you know one by one so that every time you will work on the same task again on a new set of data, remember and use the algorithm that gave you the best results last time. You can use the same process for both classification and clustering-based problems to select the best machine learning algorithm.

## Steps You Need To Select The Best Machine Learning Algorithm

There are some more methods that you can use to choose the best machine learning algorithm depending on the task on which you are working on. Let’s say you are working on a new problem that you have never gone through before so in this situation just follow the steps mentioned below to select the best machine learning algorithm:

- First, determine what type of problem you are working on, is it classification, regression or clustering?
- Then you need to make sure that you know about what are labels according to the problem statement. Labels are the values that you need to predict.
- Then according to the task that you are working on, search for the assumptions and properties of each algorithm that can be used in your problem and find the best algorithm that can give you an optimal solution.
- Finally, use the best-suited machine learning algorithm to solve your problem.

If you want to use a shortcut to choose a machine learning algorithm, you can use the PyCaret model which ranks all machine learning algorithms based on performance evaluation *metrics*. You can learn how to use the PyCaret model to select the best machine learning algorithm from ** here**.

### Summary

In this article, I introduced you to how to choose a machine learning algorithm according to the problem you are working on. As I have not been too much technical here so I hope you have understood how to select the best machine learning algorithms. I hope you liked this article on how to choose a machine learning algorithm. Feel free to ask your valuable questions in the comments section below.