What users are saying about
9 Ratings
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Score 9.5 out of 100
17 Ratings
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Score 9 out of 100

Attribute Ratings

  • IBM Watson Machine Learning is rated higher in 1 area: Likelihood to Recommend
  • Keras is rated higher in 1 area: Support Rating

Likelihood to Recommend

10.0

IBM Watson Machine Learning

100%
2 Ratings
8.2

Keras

82%
6 Ratings

Usability

IBM Watson Machine Learning

N/A
0 Ratings
7.7

Keras

77%
2 Ratings

Support Rating

4.0

IBM Watson Machine Learning

40%
2 Ratings
8.2

Keras

82%
2 Ratings

Likelihood to Recommend

IBM

IBM Watson Machine Learning is an AI-based scalable self-learning model for any type of business. It can be used to help any company automate repetitive tasks, predict future trends, and make data-driven decisions. I used it to predict stock prices based on certain variables. It works well, cost me nothing, and gives me the ability to create my own AI-based models that I can use for any purpose.
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Open Source

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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Pros

IBM

  • Good machine learning tool
  • Easy integration
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Open Source

  • 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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Cons

IBM

  • Proper usage of REST API documentation is missing.
  • Not localization friendly, cannot support regional or local language documents.
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Open Source

  • 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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Pricing Details

IBM Watson Machine Learning

Starting Price

Editions & Modules

IBM Watson Machine Learning editions and modules pricing
EditionModules

Footnotes

    Offerings

    Free Trial
    Free/Freemium Version
    Premium Consulting/Integration Services

    Entry-level set up fee?

    No setup fee

    Additional Details

    Keras

    Starting Price

    Editions & Modules

    Keras editions and modules pricing
    EditionModules

    Footnotes

      Offerings

      Free Trial
      Free/Freemium Version
      Premium Consulting/Integration Services

      Entry-level set up fee?

      No setup fee

      Additional Details

      Usability

      IBM

      No answers on this topic

      Open Source

      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.
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      Support Rating

      IBM

      IBM had a hard time providing business level support. There were a lot of data scientists and technology experts but rarely a simple business person shows up. Also the way IBM operates IBM Consulting has competing priorities as compared to IBM Technology. This has resulted in a lot of confusion at the client's end.
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      Open Source

      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.
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      Alternatives Considered

      IBM

      We have been using Microsoft Azure as a machine learning tool. But the challenges remain the same. These are all tools that you need a robust analysis before a decision on the tool. Unfortunately, the technology company cannot make that determination due to lack of core business understanding. Without that the project is doomed.
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      Open Source

      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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      Return on Investment

      IBM

      • Create secure business environment.
      • Save upto 90% of manual labor.
      • Improve my sales and marketing ROI.
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      Open Source

      • 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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