Azure AI Language vs. Keras

Best suited for large organizations, availability of usage of more than one language in a specific API call. Moderately suited for small and mid sized organizations as the pricing is on a higher end

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Keras is quite perfect, if the aim is to build the standard Deep Learning model, and materialize it to serve the real business use case, while it is not suitable if the purpose is for research and a lot of non-standard try out and customization are required, in that case either directly goes to low level TensorFlow API or Pytorch

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• The data is pre configured that means the AI models that are used by features are not customizable. One needs to send data and have to use the output of the feature in our application
• Availability of customizations in order to adjust some specific requirements
• Availability of Language studio so that one can avoid coding

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• One of the reason to use Keras is that it is easy to use. Implementing neural network is very easy in this, with just one line of code we can add one layer in the neural network with all it's configurations.
• It provides lot of inbuilt thing like cov2d, conv2D, maxPooling layers. So it makes fast development as you don't need to write everything on your own. It comes with lot of data processing libraries in it like one hot encoder which also makes your development easy and fast.
• It also provides functionality to develop models on mobile device.

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• The application is hard to use for new users
• Data Integration is complex in nature
• For Mid - sized organizations, the pricing is on higher end

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• As it is a kind of wrapper library it won't allow you to modify everything of its backend
• Unlike other deep learning libraries, it lacks a pre-defined trained model to use
• Errors thrown are not always very useful for debugging. Sometimes it is difficult to know the root cause just with the logs

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Azure AI Language has been highly effective in our product to market by reducing time spent by clinical staff with respect to patient care.

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I am giving this rating depending on my experience so far with Keras, I didn't face any issue far. I would like to recommend it to the new developers.

Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.

We haven't used other products. Our experience with Azure, whilst not meeting our needs this time around, was positive, educational and insightful. This was the first time that we had considered using an AI tool to manage and manipulate our data and we were unsure of the capabilities.

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Keras is good to develop deep learning models. As compared to TensorFlow, it's easy to write code in Keras. You have more power with TensorFlow but also have a high error rate because you have to configure everything by your own. And as compared to MATLAB, I will always prefer Keras as it is easy and powerful as well.

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• Usage of more than one language in one specific API call
• Question Answering Feature
• Key Phrase Extraction, hence one need to read the entire phrase to understand the context

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• Easy and faster way to develop neural network.
• It would be much better if it is available in Java.
• It doesn't allow you to modify the internal things.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info