Python is a powerful object-oriented language whose syntax is very easy compared to other languages. There are various GUIs that can be used to create programs via Python; developers also use it to create web and desktop applications.
Another useful feature of the language is the code, which is short compared to other languages. Because of this, the language has gained popularity.
Python is gaining more and more popularity nowadays due to its features such as ease of learning and use, which are easy, have large standard libraries, an expressive language, has a cross-sectional platform, and most importantly, it is an open source language.
Nowadays, these traits convince people to decide to learn Python in order to learn its basic features. As we know, in the future it is about artificial intelligence, which makes Python science a good option. Python is also the best language for artificial intelligence among programmers.
Also Read : 20 Most asked Python Programming Examples
Table of Contents
Artificial intelligence by Python
It is a technology in which artificial intelligence is developed for various machines, such as autonomous cars. Many other things have been developed, and many scientists are interested in this technology to develop more useful equipment.
Languages good for artificial intelligence
There are many programming languages that can be used for AI. Let’s see some of them and the reasons for choosing Python.
- LISP
The LISP language supports AI, and developers learn about it after searching at many universities. In research, prototyping was preferred, rather than execution. Other features that were preferred for AI were garbage collection, dynamic writing, functions, uniform syntax, etc.
- PROLOGUE
Prologue is a high-level language that also has LISP features. This language can be used to solve logical problems. One of the things to learn is IHMO, which is very difficult.
- C / C +++
These languages are used when the execution speed is faster than the prototyping speed. There are some applications that are small and require faster execution speed.
- JAVA
JAVA also uses many things from LISP for AI. One of them is garbage collection. The speed of starting the Java program is slow and is not at a high level compared to LISP or PROLOG.
- Python
Python also uses many LISP and Java functions. Most things between Lisp and Python are common. Along with this, JPython has Java GUI functions. JPython can also be used to create portable GUIs and this is the reason why it is best for AI compared to other languages. JPython also has the option of using HTTP / FTP libraries.
Advantages of Python compared to other languages
There are many advantages of Python compared to other languages in the case of AI. Some of them are listed below.
- – The quality of language documentation is good.
- – The language is platform independent.
- – The language is simple compared to other languages. Even a new programmer can easily learn it.
- – There are many libraries in the language that a programmer can use to create various types of applications.
- – The most important features for AI are portability, design and fast performance, and all of this exists in Python.
- – Python can be used for many types of applications, such as science, mathematics, internet applications, etc.
Also see : Python Operators Guide – Trenovision
Python for machine learning
Machine learning is something that a machine is intelligent to perform tasks such as automatically sending emails, controlling spam and other such tasks. The main job of the learning candidate is to understand the data algorithm by processing, defining, cleaning and organizing the data.
Python is considered the best for machine learning because the language is easy to learn. Python helps in implementing various concepts such as linear algebra, calculus, etc. Machine learning depends on the task to be performed, whether it is small or large. Data can be raw and unstructured, but Python can handle these things easily through various packages.
packages
This language has many packages that can be easily used to create applications. The programmer just needs to incorporate these packages into their code and use the features to help create good applications. A programmer who knows the basics of using Python can easily implement these packages in his code.
The only problem with Python’s machine learning is that it needs a lot of memory, and computers with small processors can’t use this language.
Comparison of Python with other languages
Now let’s see which other languages can be used for machine learning and find out if Python is better?
- R language
The R language is an advanced version of the S language and is used to create applications for statistical and graphic data. This language is younger compared to Python and is used in scientific research more than in machine science.
- C language
This language is considered the mother of all languages, which helps developers build various types of algorithms. This language is currently used to create a strong computer foundation.
- Python
Python is considered one of the most basic languages that can be used for a variety of purposes, including machine learning. Python has a huge amount of libraries that can be used to work on machine learning.
Why Python for machine learning?
Python is a very popular language and research has shown that about 57% of programmers attach great importance to this language when it comes to machine learning. Let’s see why this is good for machine learning.
Easy syntax
The language syntax is very simple and even beginners can learn it. Python code can be executed at high speed. Machine learning has a complex algorithm, but you can easily write it in Python.
Built-in libraries
Machine learning can be easily implemented through the various libraries present in Numpy and Scipy are the most commonly used libraries. For machine learning, the main libraries that can be used are TensorFlow, Microsoft CTNK, Apache Singa, Keras, Scikit Learn, PyTorch, Pandas, Theano, and Caffe.
Summary
It can be said that Python is very easy to learn, and machine learning algorithms can be easily implemented by it. The language has various libraries that will be useful for learning and implementing machine learning. Programmers prefer Python compared to other languages.
Also read : What is IronPython ? History of IronPython
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