Best Machine Learning Programming Language for Data Science : 2020

Best Machine Learning Programming Language for Data Science

21 century , Best time for Data Scientist . Information Technology is every where . If you want to find restaurant near you , Google is going to help you . If you are searching washroom around you , Google is again here . So what is the next generation Technology trend ? You know the answer that is Machine Learning . In fact , In the current time there are software for all most every sector . The pain area is every software is not intelligent . It can not learn . We can not train them .Only few are intelligent like Google robot . So people are trending to migrate their Non Intelligent platform to an Intelligent one . For this developers are looking for Best Machine Learning Programming Language .

My Question is to you “Are you also One of them ?” . If yes then join this conversation . This article contains enough information to select you the best machine learning Programming language for you dream application .If you want to explore more on Basics of Machine learning , Our article What is Machine Learning can help you in better way .

Best Machine Learning Programming Language for Data Science-

When you play with the data , You must need a programming language . When it comes to select the best programming language . There are so many factor which comes to picture –
1. How easy are the Syntax .
2. Community Support on that language .
3. Documentation of API available
4. Performance of the programming language .

We have tried to map all these factors to each popular machine learning language and prepare a overview for you . Lets look into that –

1. Python  –

Python is a multipurpose , High performance language . Most of the developer are migrating into python .Their Migration is itself a proof of up tend of python . Python as a machine learning language is always a attraction point for discussion in communities of data science . If you are active in any data science forum you can also experience this . Python comes with great Tool suite . From ANACONDA data science plateform to basic level interpreter , Python is very rich . If you want to take 5 minutes overview in python , You may refer our article Essentials of python in 5 minutes  . This article may give a brief over view on python .

Machine Learning Programming Language -python
Machine Learning Programming Language -python

2. R –

You can use R when you want to go more on Statistical Approach and graph analysis . Great community support is plus with R as a platform and Machine Learning Language . If we consider software tool suite for developer ease , R is one the best . R studio comes with awesome features and high compatibility with Lot of market plugins .

Machine Learning Programming Language -R
Machine Learning Programming Language -R

3. Julia –

I know the name above were most well known . Julia is new . But Julia is not only latest among them but it is really faster . Julia is dynamically typed as python . It is syntax friendly . It is quite compatible with other programming language .

Machine Learning Programming Language -Julia
Machine Learning Programming Language -Julia

4. Matlab /Octave-

When there will be machine learning , Featured Matrix is automatically available . As you also know MATLAB is best to deal in MATRIX . Even if you are beginner , I believe MATLAB is going to be the easiest platform for you to start with . If you want to explore MATLAB as  Machine Learning Language and need a tutorial for help . No need to search more here you can get Andrew Ng  video lecture on Machine Learning with MATLAB. This is  of the best resource available for your search .

 

5. Java –

I need not to introduce java . Java is one of the biggest name in the field of Information Technology . I personally love to write code in java but Here is a different context . We are looking java as Machine Learning Language . When it comes to take consideration  into a programming language performance comes first . Java family is rich of frameworks which make application faster and light weighted . Java has Weka and MAHOUT Machine learning  Library .

Hadoop  is a java framework . Most of the machine learning application is on big data . this is also a cause of popularity of java as an machine learning language .

 

C & C++  as Programming Language –

Do you know Python and many other are built on C . C is one the the fastest programming language . Its quite close to Machine language . The only reason is to put it behind that its syntax are little hard .

Machine Learning for Non Programmer –

If some body is a non-programmer and wants to learn Machine Learning . I have good news for them . They can use WEKA GUI .  Here everything related to Machine Learning is available. You can provide parameter and tune the machine learning model. See I do not mean that you can customize any machine learning model without knowing programming language but you can achieve 80 % access to what is generally required in Machine learning .

Conclusion –

Every Application is different , You should choose you programming language which suits to you application with their functional and non functional requirements .

If you ask me , At my personal level I recommend to go with python . Even I have migrated my self from Java to Python .If you want to explore more on Python capability , We have a article Python for Data Analysis . Just go through it . For me , I love python because of its library for machine learning .

If you like this article do not forget to comment your views below . Data Science Learner as Team love your comment .If you think that You need to be updated with such updates on Machine Learning and Data science , Do not forget to subscribe us .

Data Science Learner  Team

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Meet Abhishek ( Chief Editor) , a data scientist with major expertise in NLP and Text Analytics. He has worked on various projects involving text data and have been able to achieve great results. He is currently manages Datasciencelearner.com, where he and his team share knowledge and help others learn more about data science.
 
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