Today, a number of Python Frameworks for developing applications can be suggested. Using these frameworks, applications related to topics like Machine Learning, Computer Vision and so on can be created. It might be difficult for the developers to choose one of these frameworks. But the thing to be considered while choosing the perfect framework for your application will be the scope and the applicability of the application. Here is our list of 7 best tools and frameworks to build Python and AI Applications
PyQt is one of the most easy to use free cross platform GUI toolkits to create applications using python coding. With its easy to use methodology, it becomes easier, even for a backend developer, to use PyQt in dire need. It supports MacOSX, Windows as well as Linux. It contains a huge set of useful classes, functions, text editor and widgets to create the most effective GUI for any application.
Flask is the perfect open source framework to build web based machine learning applications. It can embed python code into the web programming codes. Flask is highly popular in the Python community of full stack developers. It provides great integration of web technologies with the codes written in python. A number of repositories are available on GitHub where you can find examples to get started as a beginner.
PySide is a cross platform open source GUI toolkit famous amid python developers who want an alternative to the Tkinter package library. It is best suited for building commercial projects. The UI integration has a support of all the Qt bindings. PySide supports MacOSX, Windows and Linux. The PySide team is currently working on developing the Android supportability also.
WxPython is a dynamic GUI toolkit for developing applications. It is also a cross platform toolkit since it runs on multiple software platforms. WxPython programs are easy to write and understand. WxPython also contains many widgets to create applications at a faster pace. The modules of wxPython contain a wxObject class that is the base for the whole API. Another module named Control Module is used to control all the GUI widgets in application development.
Django is a scripting text used for developing web applications. Django has Model template view architecture. A Django project may require a number of steps for installing and crosschecking that the setup is properly installed and is viable to use now. Django is capable of including many tasks such as naming the callable objects, generating the HTTP responses. The Django framework uses MVC architecture. Django also provides some optional features to create, read, update and delete interfaces that is called dynamically through examination and are configured by using administrative data models. Companies like Instagram, Mozilla, The Washington Times, Disqus, Bitbucket, Nextdoor, Pinterest use Django for web interfacing.
CubicWeb is a toolkit that is used to create customizable views of python applications. It is a semantic web application framework. It uses high reusability of numerous components by using an object oriented principles. It is highly flexible and powerful and relies on the data model of the application. It uses a query language RQL, similar to SPARQL.
Amazon Machine Learning
AML provides infrastructure for machine learning applications. Amazon Machine learning platforms provide excellent services and products to build machine learning applications from scratch. It offers services like data storage, AWS connectivity, fully-managed AI platform, Cloud Connectivity etc. With these Amazon AI services provides top notch labs and instructional application services that helps a developer to build, train and deploy the application with ease.
Here we have listed 7 best tools and frameworks to build Python and AI Applications. These tools are highly recommended for developing python application in both commercial as well as academic domains. These tools are very useful for any full stack Python developer who wants to create own applications.