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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Keras

    Score7 out of 10
    N/AKeras is a Python deep learning libraryN/A

    Quantum Boost

    N/AN/AQuantum Boost is an advanced online platform that uses artificial intelligence to reach set targets through the fewest possible experiments. Key features: Faster than DoE: Quantum Boost uses AI algorithms to ensure targets are achieved in the fewest amount of experiments possible. Flexible project development: Ability to update project definitions without losing all the knowledge gained so far, unlike most DoE software. User-friendliness:…

    $95

    per month

    Pricing
    KerasQuantum Boost
    Editions & Modules
    No answers on this topic
    Trial
    $0
    14 days
    Starter
    $95
    per month
    Enterprise
    Custom
    per year
    Offerings
    Pricing Offerings
    KerasQuantum Boost
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Best Alternatives
    KerasQuantum Boost
    Small Businesses
    TensorFlow
    Score7.6 out of 10
    TensorFlow
    Score7.6 out of 10
    Medium-sized Companies
    Google Cloud AI
    Score8.7 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    Google Cloud AI
    Score8.7 out of 10
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    KerasQuantum Boost
    Likelihood to Recommend
    8.1
    (6 ratings)
    -
    (0 ratings)
    Usability
    7.7
    (2 ratings)
    -
    (0 ratings)
    Support Rating
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    KerasQuantum Boost
    Likelihood to Recommend
    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
    Incentivized
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    Pros
    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.
    Incentivized
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    Cons
    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
    Incentivized
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    Usability
    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.
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    Support Rating
    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.
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    Alternatives Considered
    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.
    Incentivized
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    Return on Investment
    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.
    Incentivized
    Read full review
    Quantum Boost Ltd
    No answers on this topic
    ScreenShots

    Quantum Boost Screenshots

    Screenshot of Editing a project definitionScreenshot of Generating suggestionsScreenshot of Completed generation of suggestions with the probability of reaching targetsScreenshot of Adding a categorical factor to the organizationScreenshot of Editing the project spreadsheet for experimental valuesScreenshot of Analytics