This document compares Python and Go programming languages for machine learning. It discusses that while Python has traditionally been very popular for machine learning due to many libraries, Go is gaining popularity due to its faster performance, concurrency, and compiled nature. The document then outlines specific benefits of using Go for machine learning like its AI libraries, exceptional computation speed, and minimalistic yet readable code. It concludes that both languages have pros and cons for machine learning and hiring a Golang developer could help discover more possibilities.

1. P y t h o n V s . G o :
W h i c h O n e i s
a n O u t s t a n d i n g
P e r f o r m e r f o r
M a c h i n e
L e a r n i n g ?
www.bacancytechnology.com

2. Anne is a Machine Learning
enthusiast, and throughout in her 25
years of programing life, she was
coding on Python. She thought there
could be no other programming
language better than Python for
making machines understand how to
learn.

3. In my conversation with Anne when I
asked, what is Machine learning?
She replied,“Machine learning is a
subset of Artificial Intelligence,
which, in simple terms, is a science of
getting things done by computers
without directly programming. This
way, the machines(computers) learn
on their own by studying algorithms
and statistical models.”

4. She was in love with her life, enabling
machines to learn; because she had
the best tool in hand- Python. The
incredible benefits she accumulated
by choosing Python proved to be vital.
If you are wondering, “Why Python is
best for Machine Learning?”
Here are the top 3 benefits of using
Python for ML.

5. Why Use
Python
for
Machine
Learning?

6. Python is a highly readable language.
It is simple for the human mind to
understand, and hence it becomes
easy to use Python for Machine
Learning. Developers find Python
easy to learn, so they prefer to use it
over any other programming
language.
1.
SIMPLICITY OF
CONSISTENCY

7. For a big complicated machine
learning project, Python is highly
suitable because it allows
collaborative implementations from
multiple developers like Anne.
Moreover, it is a general-purpose
language, so a set of machine learning
tasks can make use of it, and
developers can build prototypes to
test their AI products.

8. The most prominent benefit of using
Python is the availability of extensive
support libraries. Specifically, for AI
and ML, Python has the following:
2.
EXCLUSIVE LIBRARIES

9. Keras, TensorFlow, PyTorch, and
Scikit-learn libraries for machine
learning algorithms
NumPy library for multi-
dimensional arrays, matrices, and
advance mathematical functions
SciPy for linear algebra,
optimization, integrations, and
stats

10. Pandas for general-purpose data
analysis
Seaborn and Matplotlib for data
visualization
Such tremendous support eliminates
the development time and overhead
for programming, providing ease to
Anne.

11. 3.
ESTABLISHED
COMMUNITY
Python has a vast ecosystem, and it
has the OSI-approved open-source
license, which makes it free to use and
distribute. The vibrant and active
community members are
continuously collaborating by
creating new libraries, updating
documentation, and extending the
toolset.

12. The Things
transformed,
obviously for a
reason

13. Anne was in total trance using the
best programming language for
Machine Learning. Then suddenly,
something happened when she got to
know that Golang is going to
overpower Python. All her thoughts
and beliefs regarding Python
changed. It happened as she came to
know about the Golang programming
language (Go). Golang is
comparatively new. It was launched a
decade back in 2009 by Google. NOT
because Python is an older one, but
just because of Go’s advancement.

14. Why Should
You choose
Go over
Python?

15. Go is a compiled language, and there
are significant advantages of Gloang
development services when Anne gets
to know about developers’ new
programming inclination towards Go,
she tried her hands on this new
programming language for ML, and
the results were outstanding.

16. Simplicity
The main plus-point of Go is its
simplicity. Anne thought that Python
was simple & easy only until she used
Go because Go is simpler than
Python.

17. Compilation
Capabilities
Golang is a compiled language, and it
compiles into a single library. It is a
statically typed language, and it links
all the dependency libraries and
modules into a single binary file.

18. Here, developers like Anne need not
install dependencies on the server.
Instead, she just had to upload a
compiled file for her app to start
working.

19. Concurrency
and Faster
performance
Go uses goroutines for concurrency,
which is a resource-efficient way to
save CPU and memory. Anne is super-
impressed by the faster performance
of Go as it saves costs and resources.

20. Native
Support
Most of the tools needed for ML are
already in-built into the Go library, so
developers don’t look for third-party
libraries. Go programming language
has superficial native support for
tools that speed up the entire process
of app development. Also, the Go
community is getting strong and
reliable for any kind of help.

21. IDE &
Debugging
A significant advantage of using Go is
getting a top-notch Integrated
Development Environment (IDE).
Anne and most developers feel that in
an agile, competitive world, an IDE is
the most crucial aspect for
development as it can speed-up or
hinder the process. Golang comes
with a comprehensive IDE and
excellent debugging tools and
plugins.

22. Clear Syntax
The Go language has a precise syntax,
which makes it easy and
straightforward. No unnecessary
components are holding back the
developers on the structure. Instead,
development becomes direct and
clear.

23. Knowing such ease and usefulness of
Go, Anne thought, Go seems to be an
ideal choice for machine learning
development services and she started
implementing ML. And here’s what
she found:

24. What are the
Benefits of using
Go for Machine
Learning?

25. As mentioned earlier, Golang doesn’t
require additional libraries; it writes
everything in core. Though it provides
lesser libraries, those specific
libraries cover a broad scope of
purposes. The GoLearn library covers
data handling; Hector covers binary
classification problems; Theano is
similar to TensorFlow, and Goml for
passing data.
1.
AI LIBRARIES

26. However, Go still needs to work on its
toolkit development. It is still in
progress and has already set up a
good community on GitHub.

27. 2.
EXCEPTIONAL
COMPUTATION SPEED
Math computations are like cake
pieces for Go. Unlike Python, large-
scale projects are better suited to Go
owing to its scalability and
performance. When it comes to
complex AI computational math
programs, Go performs 20-50% better
than Python. This way, Anne was
utterly taken by the charm of Go.

28. 3.
MINIMALISTIC &
READABLE
Go follows the minimalistic approach
for its AI and ML algorithms. After the
implementation, developers of Go
create very readable code because of
this minimalistic approach.

29. The Final

30. Henceforth, both languages have
their pros and cons. Anne hopes that
this comparison will be helpful to you
while developing your Machine
Learning Solution. If you are looking
for assistance for Golang and
wondering what other possibilities
could be discovered for machine
learning, then hire Golang
developer from us to build the next-
gen-enterprise application.

31. Thank
you