Keras vs. Sisense

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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I believe Sisense is perfectly suited for any organization of any size that have access to the proper resources, as the tool is very expensive. The data connectors come in all shapes and sizes out of the box, which allows a great deal of data control within the ElastiCubes. Additionally, while the platform only runs on Windows platforms, the web application can be accessed on any client: mobile, Apple, Windows, etc. This allows a much more flexible user experience, resulting in data and dashboards reaching further than any other tool.

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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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• Customization - lots of supported and community plugins available. Users can also adjust the look and feel through JavaScript.
• Innovation - Sisense is continuing to push the envelope by developing new features through Sisense Labs.
• Customer support - the commitment to excellent customer service and ensuring organizations get the most out of their investment.

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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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• The usability of the application on mobile devices needs some improvement, especially navigation and filtering.
• Dashboards that are created by multiple users can be a bit of a hassle to share by Admins.
• If you need to embed dashboards into your website, you are require to buy a license separate from the user and platform license. This is a norm on most BI visualization tools, but Sisense can seem a bit on the high side, cost-wide.

I think the business and myself as a user has come to rely on SiSense as a dashboarding and quick ad-hoc reporting tool. I am hoping to integrate SiSense dashboards into more parts of the business in the future. We have reduced our report turn-around time for the most part from hours/days to minutes and in some cases almost the speed of thought. Reports are also easier on the eye and more easily distributed. I would also like to say that the support and professionalism from the SiSense team has been excellent.

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.

New V5 is ground floor of an exciting collection of possibilities. Weekly Sisense developers come up with new functionality that they share with us in their forums. The move to HTML5 has been pleasing in that widgets auto size themselves into appropriate forms in the board but everyone of them can be popped out to full page size to be looked at in more detail

There are very few situations when there is unexpected downtime. Mostly during development, new dashboard implementation and during upgrades. other then that there were very few crashes.

SiSense is usually performing better then other solutions even if going for complex reports/dashboards(of course within reasonable frames). I haven't noticed any bad influence on other systems, usually if something happens it stays within SiSense.

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.

SiSense's support ninjas are very knowledgeable and are exceptionally responsive. So far, all of the issues we ran into were resolved within minimum time. My sense of dealing with the support staff at SiSense is that they are very focused on not just answering your immediate question, but also to delve into the cause of the matter.

Easy and free training that allowed us quickly understand basics in SiSense and start using them. More advanced features requires some browsing through SiSense forums, but there is always support to help, and SiSense support is one of the best whith which I worked so far.

Many examples, videos and scenarios which you try on your own right away. This combined with in-person training gives you enough to utilize most of SiSense's power.

Remember to migrate the plugins. The documentation however is pretty straight forward.

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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1) Easy to use, really, there is nothing too much to say. The set up is easy and not confusing. You can use it internally or externally.

2) Customer Service, having spoken to various product reps from similar industry. Sisense rep provides you with the best support to get started, and it is really appreciated.

Product is quite easily scalable. The whole installation can be easily moved to stronger machine if needed.

• 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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• Report development time is reduced from 2~3 days to 2~3 hours.
• Report querying time is improved from 0.5~10 mins to 2~30 seconds.
• A 2-staff team delivers 10 times the BI output that we did on the old system.
• We were able to deliver BI and data analysis for all business functions instead of a very limited group of users