Python vs. R: Which Programming Language to Choose for a Career in Machine Learning?
Machine
Learning. We can call it an application of artificial intelligence
or a subset of AI. Irrespective of how we define it, it is revolutionizing our interactions
with machines. Be it digital voice assistants or self-driving cars; ML is
making services smarter, better and faster.
In purely technical
terms, it can be defined as a study of algorithms and statistical models which
can be used by computers to execute specific tasks without explicit
instructions. While doing so, such systems rely on a variety of patterns and
inferences. They also automatically learn from their experiences and make
necessary improvements. Machine Learning
is used to develop computer programs capable of accessing data and using it to
lean on their own.
Machine
Learning and Data Science are two of the fastest growing
technology employment areas.
Data Science focuses on
statistical inference and interpretability. Machine Learning, a crucial aspect of Data Science, focuses on
predictive accuracy.
When it comes to
innovative tools, both Machine Learning and Data Science focus on open source
programming languages. That’s where “Python”
and “R” come into play.
Which
programming language should you choose for a career in Machine Learning?
Let’s understand Python, R and find out which
programming language could be appropriate for a career in Machine Learning.
We’ll also explain why R
Language and Programming Certification from NetCom
Learning could be beneficial for you.
Python
& R: The “What” Parts
Python
is a software development programming language which is based on C. It is deep
and intuitive. As compared to other languages, Python is easier to learn, and
it is a great language to link your pipeline or workflow components together.
It is a useful tool to deploy and implement large scale Machine Learning. The
codes are much easier to maintain as compared to R, and it provides front line
API for Machine Learning.
Advantages:
- An appropriate choice if your project needs more than mere statistics.
- Highly accessible and easy to learn.
- Full of useful libraries for data manipulation, collection, and machine learning.
- Has great machine learning usability.
- better than R language in engineering environments.
- Its syntax is highly readable which ensures high productivity.
Disadvantages:
·
Python has fewer statistical model packages.
· Threading could be challenging.
Multi-threaded CPU-bound applications could be slower than single-threaded
ones.
R
is an open source, statistical and visualization programming language. It is
highly cost-effective and has been data scientists’ preferred language for
years. With R, it is possible to find a library for a variety of analyses. It
is considered suitable for specialized analytical work and statistical
analysis. R also lets you create brilliant data visualization reports. R, being
an open source, sees a much faster release of latest updates.
Advantages:
·
Great for data analytics and
visualization.
·
Provides fast prototyping and working with
datasets.
·
Has a variety of libraries, packages, and
tools to improve machine learning projects’ performance.
·
R’s Statistical model packages are more
comprehensive as compared to Python.
·
Suitable for exploratory work.
Disadvantages:
·
Has a sharp learning curve.
·
R algorithms come from third parties, and
you could have numerous inconsistencies. For every new algorithm, you may need
to learn new methods to model data. Every new package will require learning;
however, R's documentation may not offer much help. These factors could harm
development speed.
Python
or R, Which One to Choose for a Career in ML?
When it comes to careers
in Machine Learning, both Python and R have their advantages and disadvantages.
Learning both these languages could be a smarter option. Both Python and R can
complete the most common tasks associated with one of these programming
languages.
Python
functions better when we talk about data manipulation and repetitive tasks. R is appropriate If you need to develop
a tool for ad-hoc analysis and dataset exploration.
The choice between the
two could depend on your background, what you want to build and why you got
involved in Machine Learning to start with.
The
following facts could help:
·
As a Machine Learning language, Python is
the leader with 57% of data scientists and Machine Learning developers using it
and 33% prioritizing it for development. R's overall usage stands at 31% and
prioritization at 5%.
·
Python is preferred most by professionals
with data science as their first profession or field of study. (38%)
·
Statisticians and data analysts mostly
prefer R. (14%)
Eventually,
choosing between Python and R could also depend on your knowledge levels and
objectives. In most likelihood, going forward, you will be required to learn
both.
Why
NetCom Learning?
NetCom
Learning is an IT
and Business training solutions provider. You may explore our R
Language and Programming Certification courses for more
details.
Our Certification Training Classes provide you a
career-enriching experience.
We Teach Technology & Business. We Manage Learning.
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