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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    MXNet

    N/AN/AApache MXNet is a deep learning framework used to mix symbolic and imperative programming to maximize productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. It is free and open-source under the Apache 2.0 license.

    $0

    per month

    IBM SPSS Modeler

    Score7.1 out of 10
    N/AIBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.

    $499

    per month

    Pricing
    MXNetIBM SPSS Modeler
    Editions & Modules
    No answers on this topic
    IBM SPSS Modeler Personal
    4,670
    per year
    IBM SPSS Modeler Professional
    7,000
    per year
    IBM SPSS Modeler Premium
    11,600
    per year
    IBM SPSS Modeler Gold
    contact IBM
    per year
    Offerings
    Pricing Offerings
    MXNetIBM SPSS Modeler
    Free Trial
    NoYes
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.
    More Pricing Information
    Features
    MXNetIBM SPSS Modeler
    Platform Connectivity
    Comparison of Platform Connectivity features of Apache MXNet and IBM SPSS Modeler
    Feature
    Apache MXNet
    -
    Ratings
    IBM SPSS Modeler
    7.0
    1 Ratings
    18% below category average
    Connect to Multiple Data Sources00 Ratings7.01 Ratings
    Extend Existing Data Sources00 Ratings7.01 Ratings
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    User Ratings
    MXNetIBM SPSS Modeler
    Likelihood to Recommend
    -
    (0 ratings)
    7.0
    (7 ratings)
    Usability
    -
    (0 ratings)
    8.0
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    10.0
    (1 ratings)
    User Testimonials
    MXNetIBM SPSS Modeler
    Likelihood to Recommend
    Apache
    No answers on this topic
    IBM
    Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
    Incentivized
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    Pros
    Apache
    No answers on this topic
    IBM
    • Combine text and data
    • Provide facilities for all phases of the data mining process.
    • Use a node and stream paradigm to easily and quickly create models.
    Incentivized
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    Cons
    Apache
    No answers on this topic
    IBM
    • Has very old style graphs, with lots of limitations.
    • Some advanced statistical functions cannot be done through the menu.
    • The data connectivity is not that extensive.
    • It's an expensive tool.
    Incentivized
    Read full review
    Usability
    Apache
    No answers on this topic
    IBM
    The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
    Incentivized
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    Support Rating
    Apache
    No answers on this topic
    IBM
    The online support board is helpful and the free add ons are incredibly appreciated.
    Incentivized
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    Alternatives Considered
    Apache
    No answers on this topic
    IBM
    When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
    Incentivized
    Read full review
    Return on Investment
    Apache
    No answers on this topic
    IBM
    • Positive - Ease of decision making and reduction in product life cycle time.
    • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
    • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
    Incentivized
    Read full review
    ScreenShots

    IBM SPSS Modeler Screenshots

    Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.