Tools and AI Frameworks Used for AI Development

AI frameworks

AI Frameworks 2018 Used for AI Development

Today Artificial Intelligence (AI) is assisting many firms to develop intelligent, smart and result-oriented AI solutions to boost the productivity of their businesses. Artificial Intelligence has proved to be a boon to the human with respect to advanced technologies.

With the help of the AI, App development industry has improved the way the businesses function. Therefore, AI-integrated apps are getting smarter than ever before. AI has become the foundation of many upcoming technologies that support in faster decision-making in the business.

AI frameworks influencing industry and user experience

Due to the development of various libraries and frameworks, AI has improved the customers experience greatly in every aspect. AI-integrated App used by customers work seamlessly with an aim to offer powerful and intelligent decisions.

AI frameworks has become responsive with respect to the IT field. Top-quality libraries that are used for artificial intelligence has lots of advance feature.

With time AI has grown exponentially. Moreover, the industry itself has increased its utilization. High-end Artificial Intelligence solutions are transforming the idea into reality.

Tools and Frameworks Used for AI Development:


TensorFlow was originally developed by members of Google’s Machine Intelligence research division. Its library is used by AI developers to develop neural networks in pattern recognition in respect to its utilization.

The Aim was to develop and conduct deep learning and machine learning research in neural networks. It is coded in Python and C++ the two powerful and popular programming languages.

Talking about the pro and cons, it is certified for distributed training, but it doesn’t contain many pre-trained models and there’s no support for external data sets.

Microsoft Azure

The Aim to build Azure is to build, deploy and manage various applications and services. Microsoft Azure is a cloud computing infrastructure that deals with a giant network of data centers managed by Microsoft itself.

The internal specification of its API is built on HTTP, REST and XML. Talking about its features, it allows integration with Microsoft Visual Studio, and Eclipse. Therefore, such kind of configuration gives a developer the freedom to interact with all the services that come under Microsoft Azure.

Moreover, it supports many other programming languages, frameworks, and tools. And many of the tools include third-party systems as well. The most of the features are controlled by Microsoft Azure Fabric Controller. Therefore, to avoid the crashing the controller have the control to manage the scalability and reliability on its own.


Keras is known for its quick performance and easy experimentation. Therefore, it one of the best among all in the option. The reason is that it can run on both CPU and GPU.

Talking about Keras, it is an open-source neural network library written in Python. Apart from that, it is used for working on convolutional neural networks and/or recurrent neural networks.

Talking about its pros with respect to the developers who are familiar with deep learning, it’s easy to use and is pretty straightforward. And, its cons its data processing tools can be a burden to process for new developers on surface-level customization.

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CNTK (Computational Network Toolkit from Microsoft) toolkit is used in Microsoft products where speech recognition services are utilized such as Windows Cortana, Skype Translator.

Microsoft’s Computational Network Toolkit is a library that increases the modularization. The best part of CNTK, it is built into C++ language and can be used for automated translation and image recognition task resolution.

Its working is the maintenance of the separation of computation networks. Apart from the other working feature, it is good in providing learning algorithms and model descriptions.

The best part of the working of CNTK is that it can utilize many servers at the same time. Therefore, it allows developers to create distributed neural networks where lots of servers are needed for operations.

Bottom line…

Giants like Google, Yahoo, Apple, and Microsoft make use of some of these AI frameworks and libraries for their deep learning and machine learning projects. These frameworks are considered to be the best tools in the App development market.  Developers are developing a new solution for their clients with the implementation of these AI frameworks and libraries.

Author Bio :-  Harry william is a digital marketing expert in, a leading Augmented Reality App Development which provides AR App for Education, Real estate, healthcare, E commerce industry across the global. He loves to write on latest mobile trends, mobile technologies, startups and enterprises.

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