Top 10 Machine Learning Algorithms For Beginners

Written By

Mohammed Aman

In a world where nearly all manual tasks are being automated, the definition of manual is changing. 

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There are now many different types of Machine Learning algorithms, some of which can help computers .

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We are living in an era of constant technological progress, and looking at how computing has advanced over the years, we can predict what’s to come in the days ahead.  

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Here is the list of Top 10 commonly used Machine Learning (ML) Algorithms: 

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Linear Regression

In this process a relationship is established between independent and dependent variables by fitting  them to a line


Logistics Regression

It is used to estimate discrete value(usually a binary value like 0/1) from a set of independent variables.


Decision  Trees

This is a supervised learning algorithm that is used for classifying problems which uses spilt method to find set of independent variables


SVM  Algorithm

In SVM algorithm, we plot raw data as points in an n-dimensional space(n=no. of features you have).


Naive Bayes Algorithm

A navie bayes algorithm/classifier assumes that the presence of particular feature in a class is unrelated to other features


KNN  Algorithm

This algorithm stores all available classes and classifies any new cases by taking majority vote of its k neighbors.



In this algorithm, datasets are classified into a  particular number of clusters .


Random Forest Algorithm

A collective of decision trees is called a Random Forest . To classify a new object based on its attributes, each tree is classified.


Dimensionality Reduction Algorithm

This algorithm helps you in finding the relevant data that is stored and analyzed by big companies.


Ada Boosting Algorithm

These are boosting algorithms used when massive loads of data have to be handled to make predictions with high accuracy. 

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