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Providing state-of-the-art applications by amalgamating the powers of data science, machine learning, and artificial intelligence via Python.
Created by a person named Guido van Rossum in 1992, Python is now one of the most popular coding languages in the programming world. This language is adored by developers for its simplicity and ease of use. For those who don’t know, Python is a multipurpose programming language that can be used for a variety of platforms.
It is a general-purpose language that can be used for several different applications that require extensive numerical computation and processing. With its compatibility with numerical, technical, and scientific computations, it is a perfect language for machine learning, artificial intelligence, and deep learning.
Many reasons make hybrid app development a good choice, especially for the client. Hybrid applications contain various features that can ensure the scalability and growth of the business and can make the business reach new strides. Furthermore, it does not invite the chance of big maintenance costs neither it demands extensive coding to create the app for different platforms.
Python has made coding and programming more sleek, streamlined, and easier to understand. It is a versatile language that implies that it is compatible with several platforms. Web development, machine learning, app development Pythons offers solutions for almost every platform.
Furthermore, its simple syntax makes it easier for the coder to program and makes the code simple enough to read even by someone who is not from a technical background.
Python language is object-oriented which means that everything in Python is considered as an object. These objects include data and codes that can be manipulated and programmed accordingly.
The standard library of Python is large and contains several packages and modules that possess many common and important functionalities. This means the developer does not need to type the code from the start or wants something from the library.
Python also provides the development of Graphical User Interfaces or “GUI” with the help of modules like PyQt5, wxPython, or Tk in python. It offers a number of GUI frameworks that are compatible with a range of different platforms.
Python language is easy to read, write and learn because of its English-like syntax. This English-like syntax makes the code easier to understand even for a non-technical person.
Since Python is one the most popular and most used programming languages among coders, it is backed by a gigantic community that helps to maintain its accessibility to any skill level.
Since it is a simple and easy language, the developers can dedicate more of their time to figuring out the problem instead of understanding the code and analyzing its behavior. This results in better productivity and efficient results.
Panda is one of the most common python libraries typically used for data analysis. Pandas contain a set of tools that allows you to efficiently clean, explore, and analyze a huge set of data. Some of the libraries dedicated to machine learning also use pandas data frames as input.
NumPy is another library used for python programming. NumPy is used to provide support and process numerous mathematical functions on multi-dimensional arrays. It helps to add robust data structures into Python programming and ensures complex calculations.
Scikit-learn is a free-of-cost open-source software dedicated to machine learning through Python. It is probably the most essential library in python that offers tools for machine learning. It is also used for statistical and predictive modeling with regression, clustering, classification, and dimensionality reduction.
TensorFlow is an open-source software math library that focuses on numerical computation and machine learning. Developed by Google, this library focuses on machine learning, deep learning, and artificial intelligence by providing models and algorithms for numerical computations.
Keras is a free-to-use software library that was built to develop and assess deep learning models. It provides an interface for artificial neural networks and sits on top of machine learning libraries such as TensorFlow.
Where Numpy is used for processing mathematical data, SciPy is an open-source library of python used to process mathematical as well as scientific and engineering data. SciPy includes modules for linear algebra, interpolation, integration, special functions, and numerous other tasks traditional in science and engineering.
Aside from all the Python dedicated libraries, we also have a fleet of more than 50 pre-built libraries that we have created with years of work experience. These libraries help in formulating the code much easier and faster.
Django is an open-source python based web framework that focuses on the development of websites. Launched by the Django Software Foundation, this framework is capable of formulating high-grade websites that are secure and easy to maintain.
Web2py is another web application framework used in Python programming. It is open-source software that allows coders to develop dynamic web content via Python programming. It is a full-stack framework which means it can be used for both back-end and front-end programming.
The bottle is a WSGI micro web framework used in python programming. It s originally created to build APIs but later proved its worth web development. It is a simple, quick, and lightweight framework that is shared as a single file module without any dependencies.
LargeTon believes in quality over quantity, and we focus on making each and every app capable of delivering exceptional performance. We efficiently push the product through the entire app development lifecycle and Fastrack the process with our pre-built libraries. We deliver best-in-class applications using Python that are the epitome of friendly user interaction and reach the pinnacle of performance efficiency.
Curating an application mobile or web is a long process and the entire process from planning to delivery can take quite a bit of time. This long duration can hamper the organization’s growth as other competitors might lunch their applications first, resulting in the loss of that competitive edge.
To tackle this obstacle, we have developed several pre-built libraries that contain packets of pre-written code specific to certain features and functions. This drastically reduces the coding time and allows us to deliver the product in a much shorter timeframe.
Python development takes less time if compared to other methods of programming. However, developing an application from python can still demand a few months to get ready for delivery and launch.
Generally, developing an application using python can take from 4 to 6 months to get ready for deployment.
There is a pool of different apps that use python as one of their primary programming languages. Many big giants like Facebook, Dropbox, and Spotify are in on the Python train. Like your Netflix recommendations? Python is the one you should thank.
Python is a relatively easy app to code and read. However, despite this merit application development with python can take some time to get ready. App development requires several different features that need to work in a coordinated manner. Hence, making a sleek and smooth app can take from 4 to 6 months.
Similar to the other programming languages, Python too asks for a hefty amount for developing an application. An application requires various other frameworks and programming languages besides Python. So, the cost of the development of an application using Python is not that different from other languages.
Python can be used pretty much anywhere, it is a very versatile language that can be used with multiple platforms and for several purposes. Mentioned below are the fields where Python programming is being used today.
Python is arguably the most preferred language in the IT industry, and there are many reasons behind it.
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