Python has enjoyed a steady rise to fame over recent years and is now jostling for the position of one of the most popular programming languages in the world. Favoured for applications ranging from web development to scripting and process automation, Python is quickly becoming the top choice among developers for artificial intelligence (AI), machine learning, and deep learning projects.
The high-level, robust programming language focuses on rapid application
development. The core functionality has helped Python become one of the fastest-growing programming languages. Here are top reasons why developers and
companies working on emerging technologies including AI, and ML tend to choose
Python.
Simple code structure:
Python focuses on reducing the number of lines of code that you write to
execute a function. The language simplifies the code and makes it readable. The
combination of Python and AI will help in reducing the size of code that
developers write. The language, if used with AI and ML algorithms, will make it
easier to reduce the quantity of code.
Vast Community:
Python is well-known for its extremely vast community. Since its
release, the community is contributing largely and which is the reason a Python
user never feels abandoned with sudden changes. The constant upgrade by the
developer community support makes Python one of the most suitable languages for
machine learning applications. Large organisations such as Google, Amazon,
Facebook, etc. are using this language.
Frameworks & Libraries:
One thing the developers like most about Python is the abundance of open
source libraries and frameworks. The language has a great number of machine
learning libraries and some of the prominent libraries are such as TensorFlow,
Pytorch, Matplotlib, SciKit Learn, etc. Python has a collection as well as code
stack of various open-source repositories in almost every domain such as Django
for integrating web applications, pandas for machine learning, SciPy for
scientific computing, Librosa for audio, OpenCV for images, NumPy for text,
etc. Other commonly used libraries for artificial intelligence and machine
learning are such as pyDatalog (Logic Programming engine in Python), PyML (the bilateral framework is written in Python that focuses on SVMs and other kernels methods), EasyAI (Simple Python engine for two-players games with AI), PyBrain
(simple and effective algorithm for ML tasks), AIMA (Python implementation of
algorithms), simple, etc.
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