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Top 10 most popular machine learning languages in 2018 revealed

New Delhi, Tue, 18 Sep 2018 Deepak Kumar

Research reveals top 10 most popular machine languages used by data scientists in 2018 around the world. According to the Tech Pro research Python is most popular programming language used by data scientists around the world for developing machine learning and data science project in 2018. Python programming language shared 61% share in the Data Science programming field.
According to the Figure Eight report 90% of data scientists are working on machine learning projects in one or other way during involvement on the data science project. More and more data scientists are experimenting with the multiple machine learning technologies to find most efficient solution to a problem. Companies started collecting their data on the Big Data platform and looking towards solution for analyzing their data. Here comes the role of Data Scientists to work with huge data sets and develop solution to analyze it. With the help of machine learning technologies data scientist are analyzing vast data sets and produce insight of company data.

Due to high demand of development of data analysis and machine learning software there is big demand of skilled data scientists. According to a research every data scientists are getting at least one calls for job in a week.

 In America data scientist job are very lucrative career as most of the skilled data scientists are getting decent salary as compared to other IT fields. Companies are paying top salary to data scientists in the IT industry. Data Scientists job are number 1 job on the Glass doors Best Job in America keyword for the last 1 year.

According to the Figure Eight report job satisfaction among data scientists are 89%, which grown from 67% in last 3 years (from 2015). These figure shows that the job prospects in the data science and machine learning field is very bright.

Moreover demands of skilled data scientists are very high in American and world IT market. That’s why developers around the world is learning this demanding technology.

Data Science and Deep Learning technologies are relatively new technology which is getting momentum due to wide acceptance by industries. Industries are moving their data on Big Data platform for further analysis. There are many tools and frameworks for machine learning, but these are still no wide consensuses on the use of technologies to use. Developers are learning and trying various languages to match their business requirement.

In most cases developers adapts to Python as programming language as this language is easy to learn and there are many pre-build machine learning libraries for this language.
According to Tech Pro research 61% developers are using Python programming language as machine learning framework for their projects.

Here are the lists of top 10 machine learning programming languages used by data scientist around the world:

  1. Pandas
  2. Numpy
  3. Scikit-learn
  4. Matplotlib
  5. TensorFlow
  6. Keras
  7. Seaborn
  8. Pytorch & Tourch
  9. AWS Deep Learning AMI
  10. Google Cloud ML Engine

These tools and programming languages are evolving fast and new versions of the software are getting released frequently with improvements. New versions of each library come with new features, bug fixes and performance improvements.

From the above list of top 10 most used machine learning programming languages shown that the developers are interested in the open source languages and tools. Most of the above tools are open source.

--Deepak Kumar

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Author: Deepak Kumar

Deepak Kumar is Science Graduate from Delhi University with more than 18 years of experience in Technical field. Currently his interest lies in researching for Media and Journalism field. He has years of rich experience in various technological fields. With a background in Science and Media field, Deepak has been offering services in the media houses and technical research. He has worked as director and chief in many companies. As a technical writer, editor and reviewer, he is offering services to many research organizations, media houses and online educational portals.

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