# MACHINE LEARNING : ALGORITHM AND MODEL EXPLAINED

For all the beginners out their, it is very confusing to figure out the difference between machine learning algorithm and machine learning model.
And we will try to understand the major difference between them in this article.

WHAT IS MACHINE LEARNING ALGORITHM:-
An algorithms is a step by step approach powered by statistics that guides the Machine in its learning process.
The machine learning algorithm is run on a set of data, to bring machine learning model into existence.
There are different types of algorithms for classification in machine learning,
For example :
a) K-Means
b) Decision tree
c) K- nearest neighbours
d) Linear Regression
e) Logistic Regression
f) Artificial Neural Network

Some other algorithms which we commonly know include,
a) For searching- “Best search”.
b) For data sorting – “bubble sort”.
Some of the properties of machine learning algorithms are :
a) Algorithms can be used with any of the modern programming languages.
b) Algorithms can be described using pseudocode and math.
c) Their efficiency can be described and analysed.

Algorithm treats all the data same. But it is the model that actually solves the problem at hand. Same as a teacher, who teaches every student equally, but not every one tops.

WHAT IS MACHINE LEARNING MODEL:-
The model is the output of the machine learning algorithms.
It is on the other hand dependent upon many factors such as feature, selection, tuning parameter, cost function etc along with the algorithm.
Let’s take some examples to understand it;
a)The decision tree algorithm, results in model, comprised of a tree of, it and if statements with specific values.
b)The linear regression algorithm results in a model comprised of a vector of coefficients with specific values.

The machine learning model “program” is comprised of both data and a procedure for using the data to make a prediction.

MACHINE LEARNING IS AUTOMATIC PROGRAMMING:-
Machine Learning is something which has helped us to reduces our work load to a great extent.
It has allowed us to do all the fragile, time taking and tedious work within a fraction of seconds.
Let’s take an example of email,
We convey and do lots of our important messages through emails, We get lot of important mails and a lot of spam mails too. What if, Differentiating useful mails and spam mails was all up to us? It would have been a great headache. But because of machine learning we can do it in a fraction of seconds with the techniques to solve this problem Specifically, an algorithm named as NAIVE BAYES is their, which can classify email messages as spam and not spam from a large dataset of historical examples of email.
The machine learning algorithms perform automatic programming.
Hope that after reading this article you would have been able to understand the basic difference between Algorithm and Model.

In nutshells, we just tried to understand:-
1)That algorithm is run on a data to create a model.
2) A model comprises of both data, and the process for how to use a data, to make forecasting on a new data.
3)Machine learning algorithms provides a type of automatic programming whereas machine learning models represent the program.

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