Syncfusion Essential Studio vs. TensorFlow

The datagrid is probably their most popular control I would think. It is so flexible and configurable. Most of mine are plain views in ASP.NET Core, but I have a whole bunch that are dynamically created at runtime in my controller. That is so powerful.

TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).

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• Integrates well into Microsoft tech stack. i.e. ASP.NET, Blazor etc. So it acts as a plug-n-play, which is great!
• Shrinks the development cycle without adding too much of its own ecosystem overhead.
• Provides different UI skins so the controls don't appear as "stitched".

• A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
• Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
• Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.

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• Sometimes links point to dead addresses in the documentation.
• Some components have a difficult learning curve but that is usually due to the complexity of the control.
• Minor version changes introduce breaking changes, for example updating from 20.1.x to 20.2.x gives us licensing errors, which in my opinion is a kind of breaking change as it requires all users to update their licenses.
• Theming with CSS variables is not possible. Access to Theme Studio code is not possible. So a fully custom solution is needed to make Syncfusion Essential Studio Enterprise Edition components themeable with CSS variables.

• RNNs are still a bit lacking, compared to Theano.
• Cannot handle sequence inputs
• Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.

It takes effort to include a new component library into existing software, especially in our case where we have 5 large applications that are written and maintained by about 100 developers. So changing such a core thing comes with a lot of effort. The other reason we will very likely renew our use of Syncfusion Essential Studio Enterprise Edition is that it works really well and has helped us to speed up the development process.

I would rate Syncfusion® Essential Studio® a 10 out of 10 for overall usability. The components are intuitive to implement, with clear APIs and consistent design patterns across the suite. This makes it easy for developers to get started quickly and reduces the learning curve even when working with new controls.
In addition, the documentation and sample projects provide practical guidance that helps accelerate development. The built-in customization options also allow us to adapt the components to fit our branding and business requirements without excessive effort. Overall, the usability is one of the key reasons why Syncfusion has become an essential part of our development toolset.

Support of multiple components and ease of development.

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Although I have decades of software development experience, I had never created a website from scratch before, and my html and css skills are not particularly strong. Between documentation and incredible dedication from the support team they helped me overcome all of my challenges. It's amazing that they typically create sample code for most of the issues that I submitted. On rare occasions where I uncovered a defect they kept me informed as to its status, and typically resolved it in a short-term release, and/or gave me a reasonable workaround. They hopped on zoom calls with me on multiple occasions when necessary.

Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.

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Feedback from the team has been very positive.

Use of cloud for better execution power is recommended.

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Firstly, there is a free version for small businesses and it allows you to jump start without risk. I found one of the other products a bit short in the number of out-of-the-box supported events handlers for each control and, although you can manually add them, I feel more comfortable to just have them ready. After using the free version I just felt in love with Syncfusion Essential Studio Enterprise Edition controls and decided to stay with them; they have all I need and more. The usage of Syncfusion Essential Studio Enterprise Edition controls is straightforward and intuitive. Support is world-class even for the free version; you get answers in 24 hours at most. Also, the support team is ready to remotely connect to your project in case it is needed; we have had one situation like this, and the issue was solved.

Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice

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• First of all, I think the best positive impact is the reduce of time development. I do not know exactly how much time, but certainly, using the framework we save a lot of effort and time.
• About negative impact, sometimes using the controls of the framewrok have a signifcant impact in the execution time and page load.
• And of course, the use of Syncfusion Essential Studio Enterprise Edition has a significant impact of the learning of javascript and JQUERY.

• Learning is s bit difficult takes lot of time.
• Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
• Once you have learned this, it make your job very easy of getting the good result.

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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