In today’s market where competition is at its peak, we need to expand our skills as fast as we can to survive in the IT
industry. In this regard, we can’t spend so much time learning all the programming languages which support different
technologies. Python is the solution for all those challenges where you can implement many technologies. By doing this,
we can save our time to write big syntax and get the solutions easily.
Python has libraries for visualization, statistics, natural language processing, image processing, data loading and
more. This vast toolbox provides data scientists with a large array of common and special purpose functionality.
Reasons for using machine learning in python:
- Scikit learn (scikit-learn: machine learning in Python) is the best source for machine learning algorithm here
you will get every ML algorithm on python. : Scikit is a simple and efficient for data mining and data analysis
built on numpy and matplotlib which make it more useful for many application In machine learning
- Python is very easy to understand and write code, not only for machine learning but also for analytics,
programming, web development, statistical analysis. : Python syntax is very easy to write and understand that is
the reason now python is a first preferred language to learn and to understand the basic concepts of procedural
and Object-oriented programming. This raises the boundary of technologies we can use with python for different
purpose i.e. web development and statistical analysis.
- Easy to get support library for python: Python is a library rich language, which makes it more popular in
comparison to others. Python inbuilt libraries are written in C and C++ and they are well optimized to run fast.
- Has many modules to support machine learning applications: Python has many modules such as NumPy, Keras,
TensorFlow, Pandas, PyTorch and Matplotlib which make it more useful for different purposes.
- Code style in python: Readability of python codes is very easy. Arguments can pass to the function in different
ways. Short way to manipulate the list. Reading from a file has very less syntax
- Easy to get help on the internet because the Python community is vast and insanely strong. : Python is an open
source language that has a very big community to give you answers for your challenges It has a very strong
approach to solve any problem with less hard work. The syntax is more Chrystal clear than any other programming
Credit: Stack Overflow
- Python codes for machine learning are very small as compared to any other language: Python programs are
typically 3-5 times shorter than equivalent other programming languages. This difference can be attributed to
Python's built-in high-level data types and dynamic typing. For example, a Python programmer wastes no time
declaring the types of arguments or variables, and Python's powerful polymorphic list and dictionary types, for
which rich syntactic support is built straight into the language, find a use in almost every Python program.
Machine learning popularity with python:
With respect to time and percentage of matching job postings, we can see the growth in using machine learning with
By seeing this we can say that python with machine learning is our present and probably our future also. So why waste
time let’s get start machine learning with python.