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Python and Java both lay claims to being among the top five most popular programming languages at any given time, with Java usually just ahead of Python. However, Python’s popularity is growing at a tremendous rate, and Python overtake Java in 2018.

Python is a high-level, interpreted, interactive and object-oriented scripting language. Python was designed to be highly readable which uses English keywords frequently whereas other languages use punctuation and it has fewer syntactical constructions than other languages.

Java and Python have many similarities. Both languages have strong cross-platform support and extensive standard libraries. They both treat (nearly) everything as objects. Both languages compile to bytecode, but Python is (usually) compiled at runtime.

Python versus Java:

1. Java language is more about syntax, if one can forget to add curly braces or semicolon in the end then this will show error as your output. But there is nothing like that with python there is no need of semicolon and curly braces in the end but python follows indentation process so that it will make your code readable.
2. Java programming is statically typed means that one has to explicitly mention the data type of variable. If datatype (int, float, double, character) isn’t mentioned then the error can occur in program. Python is dynamically typed means if one has directly assigned a value to a variable at the runtime then it'll assume data type.
3. Java codes are more complex than python codes. Try to write a hello world program in both then you'll observe the complexness of the code, four lines of code in Java and same hello world program in python are of 1-line code.
4. Python has a large and robust standard library makes Python score over other programming languages. The standard library allows you to choose from a wide range of modules according to your precise needs. Each module further enables you to add functionality to the Python application without writing additional code.
5. Python is an open source programing language, Python helps you to curtail software system development cost significantly. You’ll even use many open source Python frameworks, libraries and development tools to curtail development time without increasing development cost. You even have choice to select from a wide range of open source Python frameworks and development tools per your precise needs.
6. Interpreted, with tools like IDLE, you can also interpret Python instead of compiling it. While this reduces the program length, and boosts productivity, it also results in slower overall execution.
7. Python is considered to be the most favorable language for Machine Learning, Artificial Intelligence, IoT and much more.
8. Python has a more unified support model than Java for the first time, and open source developers are focusing their efforts on the latest version of the language.
9. After working on large projects in both languages, I feel secure saying that Python’s syntax is more concise than Java’s. It’s easier to get up and running quickly with a new project in Python than it is in Java.
10. The most two popular frameworks for Python are Django and Flask. Flask is a micro web framework, it gives you the basic functionalities you’d need like routing requests without much overhead. Django is a more featured option and can help you build a powerful backend while capitalizing on efficiency and security, Django is equipped with a powerful ORM layer which facilitates dealing databases and performing different operations on the data.

Python is one of the fastest growing programming languages. It has undergone more than 28 years of the successful span. Python itself reveals its success story and a promising future ahead. Python programming language is presently being used by a number of high traffic websites including Google, Yahoo Groups, Yahoo Maps, Shopzilla, Web Therapy, Facebook, NASA, Nokia, IBM, SGI Inc, Quora, Dropbox, Instagram and Youtube. Similarly, Python also discovers a countless use for creating gaming, financial, scientific and instructive applications.

Python is a fast, flexible, and powerful programing language that's freely available and used in many application domains. Python is known for its clear syntax, concise code, fast process, and cross-platform compatibility.

Python is considered to be in the first place in the list of all AI and machine learning development languages due to the simplicity. The syntaxes belonging to python are terribly easy and can be easily learn. Therefore, several AI algorithms will be easily implemented in it. Python takes short development time as compared to different languages like Java, C++ or Ruby. Python supports object oriented, functional as well as procedure oriented styles of programming. There are lots of libraries in python that make our tasks easier.

Some technologies relying on python:

Python has become the core language as far as the success of following technologies is concerned. Let’s dive into the technologies which use python as a core element for research, production and further developments.

1. Networking: Networking is another field in which python has a brighter scope in the future. Python programming language is used to read, write and configure routers and switches and perform other networking automation tasks in a cost-effective and secure manner.
2. Big Data: The future scope of python programming language can also be predicted by the way it has helped big data technology to grow. Python has been successfully contributing in analyzing a large number of data sets across computer clusters through its high-performance toolkits and libraries.
3. Artificial Intelligence (AI): There are plenty of python frameworks, libraries, and tools that are specifically developed to direct Artificial Intelligence to reduce human efforts with increased accuracy and efficiency for various development purposes. It is only the Artificial Intelligence that has made it possible to develop speech recognition system, interpreting data like images, videos etc.

Why Choose Python for Artificial Intelligence and Machine Learning?

Whether a startup or associate MNC, Python provides a large list of benefits to all. The usage of Python is specified it cannot be restricted to only one activity. Its growing popularity has allowed it to enter into some of the most popular and complicated processes like artificial intelligence (AI), Machine Learning (ML), natural language process, data science etc. The question is why Python is gaining such momentum in AI? And therefore the answer lies below:

Flexibility: Flexibility is one of the core advantages of Python. With the option to choose between OOPs approach and scripting, Python is suitable for every purpose. It works as a perfect backend and it also suitable for linking different data structures together.

Platform agnostic: Python provides developer with the flexibility to provide an API from the existing programming language. Python is also platform independent, with just minor changes in the source codes, you can get your project or application up and running on different operating systems.

Support: Python is a completely open source with a great community. There is a host of resources available which can get any developer up to speed in no time. Not to forget, there is a huge community of active coders willing to help programmers in every stage of developing cycle.

Prebuilt Libraries: Python has a lot of libraries for every need of your AI project. Few names include Numpy for scientific computation, Scipy for advanced computing and Pybrain for machine learning.

Less Code: Python provides ease of testing - one of the best among competitors. Python helps in easy writing and execution of codes. Python can implement the same logic with as much as 1/5th code as compared to other OOPs languages.

Applications of Python:

There are so many applications of Python in the real world. But over time we’ve seen that there are three main applications for Python

Web Development: Web frameworks that are based on Python like Django and Flask have recently become very popular for web development.

Data Science (including Machine Learning): Machine Learning with Python has made it possible to recognize images, videos, speech recognition and much more.

Data Analysis/Visualization: Python is also better for data manipulation and repeated tasks. Python helps in the analysis of a large amount of data through its high-performance libraries and tools. One of the most popular Python libraries for the data visualization is Matplotlib.