Top 5 Machine Learning Algorithms which is Must for You

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Machine Learning is disrupting the market rapidly .  You already know , AI is effecting the way of Production whether for Software , Auto Mobile unit or any other sector  . I am no kidding , Each Industry must have some opening for Data Scientist and Machine Learning Engineer . Its an strong evidence for Rise of AI and Machine Learning Era . Do you  also want to be future ready for Machine Learning ?I mean ! Are You looking to learn the Machine Learning algorithms ? Reading this article will end up your search for Top  Machine Learning Algorithms .

This article will give you an overview about the Top Machine Learning Algorithms . This article is design in such a way that It best suits to Data Science beginners and Intermediary Readers . All you need to read it till ending . Its just an overview article , So I have put very simple language with lots of Machine Learning Examples .  So do not skip the article Until you finish reading it .

Top Machine Learning Algorithms :

Under the Machine Learning umbrella , There are so many algorithms  paradigm . I think you should learn topic wise algorithms .

1. Regression Algorithms-

Regression algorithms are one of the common type of task which we need to perform as data scientist .See there are so many ways to perform regression algorithmically but we will put the important form of regression –

1. Simple Linear Regression
2. Multiple Linear Regression
3. Polynomial Regression
4. Support Vector Regression
5. Decision Tree Regression
6. Random Forest Regression

2 . Classification Algorithms –

1. Logistic Regression
2. Naive Bayes
3. Support Vector Machine (SVM)
4. K-Nearest Neighbors (K-NN)
5. Random Forest Classification
6. Decision Tree Classification

3  . Clustering Algorithms–

1. K-Means Clustering
2. Hierarchical Clustering

4. Association Rule Learning–

1. Apriori algorithm.
2. Eclat algorithm.

5. Reinforcement Learning–

1. Upper Confidence Bound
2. Thompson Sampling .

Why  Machine Learning Algorithms are  needed ? –

To understand the importance of a Machine Learning Algorithms , You need not  to think much Technically Just ask yourself about the best way of learning anything . Do you like learning by experiences or  If I provide you some set of rules . Obviously you will say learning from past experiences  enhance  your understanding . The same approach we apply when training Models . Rather writing the code in so many  If else block , we use some probabilistic approach . This approach dynamically choose the best path on the basis of the  past data .Frankly speaking there are some cases  where you can never write the code in just  if else  block . For example Email Spam classification . Just think about it . Here how much logic will you code for ? Obviously you need a  Machine Learning algorithms which make probabilistic  decision .

Anyways  Before You Proceed I will recommend to give you a quick look on What is Machine Learning  . It will give you a warm start with Machine Learning Algorithms . Choosing the best Algorithms can increase the accuracy and reliability  of your Model .At the last but not the least , Apart from the all this , There is also an important corner .Guess what ? Best Programming Language for Machine Learning .

How To Implement  Machine Learning Algorithm –

Once you go through the logic part of these algorithms , You must find the implementation needs too much code . But the reality is completely different from it . There are so many well designed machine learning frameworks which make our life easy .All you need to understand thier predefine library functions . You need to call them when required .

We have an amazing article on Top 5 Machine Learning Libraries . I will suggest you to read this article as it gives a deep insight on machine learning libraries .The beauty with these framework is uniform syntax throughout the code .I mean all preprocessing , evaluation , cross validation have similar syntax throughout the framework  . Even while using different model you need not to change much on codes .

Conclusion –

Choosing Right Machine Learning Algorithm is tricky . In my Data Science journey I found people are struggling in two steps –

1. In choosing Right Machine Learning algorithms
2. Deciding the correct EVALUATION MATRIX .

In the above article , we have tried to solve your first problem . The goal behind this article is to make you aware about the types and names of machine learning algorithms . If you have other name which could add on in this for best machine learning algorithms ,please suggest .

Thanks

Data Science Learner Team .

Source: Data Science Learner