Keras vs. Maple

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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Maple is very useful in following scenarios :

• When doing some equation modelling for differential equations
• Writing code to simulate a electrical of mathematical system
• Speech and Image Processing Use case
• Linear Algebra Problems
• Lot of Options to plot 2-D and 3-D, including implicit, contour, complex, polar, vector field, conformal, density, ODE, PDE, and, statistical plot
• Engineering plots, including time and frequency domain responses and root-locus and root-contour plots

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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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• Numerical Calculation and Calculus
• Visualization of statistical and numerical data
• Predefined code templates for standard problem like finding FFT

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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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• On the software side and the software is bulky
• Code Editor can be improved
• Sometime software fails and hang when doing high calculation

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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.

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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Maple is a very niche product and competes directly with Mathematica and MATLAB. It is a little expensive as compared to the other two however has more set of functions and libraries which makes it for suitable for high level and complex mathematics. It's editor is not on par with other two however it's visualization module is very good and powerful.

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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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• It saves time and does lot of hard calculation which is not possible manually
• Software is little bit expensive however has more functions as compared to Matlab and Mathematica
• Learning curve is little steep and hence take additional time to master

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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