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# The Step by Step Guide to Azure Machine Learning (Part 2)

### This post delves into the various algorithms that Azure Machine Learning uses to process data. Take a look at what scenarios the various algorithms can help with.

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In the last post, we have discussed Machine learning. Now in this post, we will discuss some more detail about algorithms and, trust me, this is one of the most important objects that a machine learning engineer should know.

These objects are nothing but the algorithms. As a data scientist or machine learning engineer, the most important things are we should know are:

• What is the data?

• What is the result?

• What analysis do you need to apply to get the desired result or prediction?

I know this is pretty much clear but let me explain with an example. Suppose, we have student data within a high school 's internal assignments and we need to predict if the student can pass the final exam or not.

Now, let me give you a brief overview of some of the algorithm types, which we may require in Azure Machine Learning. Although there are many more types (and subtypes) than we list here, we will not go in that deep. So, let's start.

## 1) Two-Class

We will apply this algorithm when the prediction results in either yes/no or true/false or 1/0. For example, can a student pass the final or not?

## 2) Classification

This is another algorithm that helps us predict answers like which Kabaddi or cricket team you will cheer on, or which political party you will vote for.

## 3) Linear Regression

This is one of the more common prediction methods. For example, in an office, you can predict an engineer's salary range depending upon last few engineers' salaries. Or, you can predict the range of a property sale by comparing prices of similar lots in the area.

## 4) Anomaly Detection

Like the name says, this algorithm is for when we need to find anomalies. For example, say you have a herd of cows. Most of them are white, but there's one black one, too. This algorithm will help you detect oddly colored cows.

I hope the all the above algorithm types are clear. In the next post, we actually do the step-by-step Microsoft Azure Learning, so don't worry about that.

Topics:
azure ,azure machine learning ,algorithm

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