Are you a future programmer in python development? If your answer is yes, then you are in the right place at right time. Because, today we are going to talk here about the future of the programming language PYTHON.

Before reading you may ask yourself at first side why is this language the future of the programming? Well, that's a difficult question to answer, because there are many applications for Python. Python is one of the languages that programmers use along with Java and Node.js. For years, they have carried out successful projects development in this language.However, there are clearly 3 more popular applications than the rest:

•       Development of the Web
•       Machine learning including data science, visualization, and data analysis
•       Gaming or, scripting

A quick over view

Python has a series of characteristics that make it very special, and that undoubtedly provide many advantages and are at the root of its widespread use. Python is a multi-paradigm language. This means that it combines properties of different programming interface. Python is cross platform, i.e., can run on different operating systems like Windows or, Linux simply using the appropriate interpreter. However, this is not a big problem. The differences in speed are small, and nowadays the bottleneck in software development projects is not in the CPU. Thanks to advances such as computing in the cloud, today we have great computing capacity at a very affordable cost.

Development of the Web with Python

You need a web framework because a web framework facilitates the creation of a common back-end logic. This includes correlating different URLs with Python code fragments, dealing with databases and generating HTML files that users see in their browsers.Professional programmers use both of them. Both of them are popular web frameworks. But, if you are a novice programmer, it would be best to start with only one (Flask). Recently, Flask, and DJango (Python-basedweb frameworks) have become an important platform for the development of the Web. These frameworks help to create server code (back-end code) in Python. That's the code that runs on your server, unlike users' devices and browsers (front-end code). Get your python training in kanpur, and learn these web frameworks under professional surveillance.

Main differences in DJango, and Flask

Flask web framework offers flexibility, simple interface, and smoother control. It is not optimized. It gives you full control over the things that you want to implement in your development. Whereas, DJango offers a relevant, but professional experience. You will get a stronger database interfaces, a professional administrative panel, an ORM, ready to use interface, and complete directory interface for the applications you need to develop. You should choose -

Flask: If you are focused on the experience, and learning opportunities, or if you want to have more control over what components to use (such as what databases the programmer wants, and how they want to communicate with it).

DJango: This is more like a professional type. Creating simple applications like an e-commerce, news site, or a blog will be better done by DJango. As a novice programmer if you need something really unique and simple way to get it done this is the platform you will need.

If you just have started to gather experience, and knowledge is the ideal option for you will be Flask. You will be dealing with fewer development components. It is obviously a perfect option if you want more customization. Finally, Flask is more suited to create these things called REST API than DJango because of its flexibility. On the other hand, if you're looking to build something simple, DJango will probably allow you to get there faster.

Machine learning including data science, visualization, and data analysis

Machine learning system works with an algorithm which generally detects the pattern in input given format. If you give 100 pictures of a table, and 100 pictures of the Dog to an automatic learning algorithm, for example. Then only it will be able to learn the difference – a table, and a Dog. When you give a new image of a dog or a table, it can recognize what it is.

You can apply the same idea to recommendation systems (think YouTube, Amazon and Netflix), facial recognition, or voice recognition among other applications. There are some most popular AI machine learning algorithms which you will be working in the future are - deep learning, random forest, support vector machines, and neural networks. You can use any of these algorithms to solve the problem of labelling dog and table images.

Python for machine learning

There are well-known automatic learning libraries, and frameworks for Python. Tensor Flow, and Scikit Learn are the two most famous platform among others. Scikit Learn is programmed with the most popular AI incorporated algorithms. Whereas, with Tensor Flow you can customized learning algorithms for the machines with basic level library. If you are starting with an automatic learning project, it is advisable that you consider Scikit Learn to start with. If you are having efficiency issues then TensorFlow could be an ideal option. But, having good experience in both the interfaces are essential because there are different platforms for different needs. Get your skills developed with machine learning training in Kanpur one of the best python training center.

Analysis / visualization of data with Python

In this segment, Matplotlib is definitely one of the greatest AI libraries that you can use for visualization of dat. It's a good library to start with because - It's easy to start with it, and some other libraries, like sea-born relies on it. Therefore, learning Matplotlib will help you learn these other libraries later on.

Scripting with Python

Writing short programwhich is designed to simple automatic tasks - known as Scripting. If you consider a relatively simple syntax, and is easy to write interface, Python is the most popular, and suitable platform in this case. It's also quick to write something small with it, and try it out.

Integrated applications: Python works with Rasberry Pi. It is a popular application among hardware fans.

Gaming and game development: To develop modern games, you can use PY-game. This is one of the most popular gaming library. But, this is not only the single option you have. You can use this as a project hobby, but it is not recommended if you take the development of the game seriously.