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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Keras

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

    Kimola Cognitive

    Score10 out of 10
    Small Businesses (1-50 employees)
    Kimola Cognitive is a Machine Learning Platform that enables users to grab reviews from 20+ channels and analyze + classify customer feedback -or any text data- automatically. Top features of Kimola Cognitive are: Scrape Web and Collect Reviews Data analysis starts with data collection, and Kimola offers a web browser extension for marketing and research professionals to scrape content from the web to analyze and classify. It supports over 20 mediums, such as Amazon, Yelp,…

    $199

    per month Query

    Pricing
    KerasKimola Cognitive
    Editions & Modules
    No answers on this topic
    Starter
    $199
    per month 10.000 Queries
    Standard
    $399
    per month 35.000 Queries
    Business
    $999
    per month 100.000 Queries
    Offerings
    Pricing Offerings
    KerasKimola Cognitive
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details—- 20% discount on annual plan for each package is available. - Pre-built ML Models are free to use for every client. - Scraping is free to use for every client. - There is no user seat limit.
    More Pricing Information
    Best Alternatives
    KerasKimola Cognitive
    Small Businesses
    TensorFlow
    Score7.6 out of 10
    No answers on this topic
    Medium-sized Companies
    Google Cloud AI
    Score8.7 out of 10
    No answers on this topic
    Enterprises
    Google Cloud AI
    Score8.7 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    KerasKimola Cognitive
    Likelihood to Recommend
    8.1
    (6 ratings)
    10.0
    (1 ratings)
    Usability
    7.7
    (2 ratings)
    -
    (0 ratings)
    Support Rating
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    KerasKimola Cognitive
    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
    Kimola Cognitive
    Since using the tool for 4 months we have been extremely pleased with its performance. I've decided to share this review after receiving an email from the Kimola Team, and once I'm in the consumer insights business, I'll definitely support them. The interface and design are fantastic, with a great choice of colors, and Kimola has consistently introduced numerous improvements to the product since we first started using it. The ease of use is unmatched, allowing us to gain new insights and perspectives that were previously unattainable
    Read full review
    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
    Kimola Cognitive
    • Despite exploring various software options to analyze client feedback, none have proven as specific and accurate as Kimola Cognitive.
    Read full review
    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
    Kimola Cognitive
    • I believe that more language support should be added and it should reach more customers.
    Read full review
    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
    Kimola Cognitive
    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
    Kimola Cognitive
    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
    Kimola Cognitive
    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
    Kimola Cognitive
    • In order to create a custom model, if you are not experienced in this field, you need to watch a video on youtube. This question has little to do with Kimola.
    Read full review
    ScreenShots

    Kimola Cognitive Screenshots

    Screenshot of After signing up, Kimola Cognitive's home page full of support articles, resources and pre-built models are displayed.Screenshot of Reports can be generated after choosing a sentiment and classification model, and with a PDF export.Screenshot of Kimola Cognitive comes with a gallery of ready-to-use Machine Learning models for the most common use cases like sentiment and hate speech analysis along with consumer conversations around SaaS products, mobile apps, games.Screenshot of Kimola Cognitive also supports creating custom Machine Learning models by training a dataset. The platform takes care of choosing the best performing statistical model to ensure accuracy. The custom machine learning models are hosted on Kimola Cognitive and can be used via the user interface and API.Screenshot of Reviews can be scraped from 20+ mediums such as Amazon, Etsy, Booking, Walmart, Reddit etc. with Kimola Cognitive's browser extension.Screenshot of Marketing materials can be created with a GPT integration, from creating SWOT analyses to product descriptions.