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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Machine Learning

    Score8.2 out of 10
    N/AMicrosoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.

    $0

    per month

    IBM Watson Discovery

    Score9 out of 10
    N/AIBM offers Watson Discovery, a natural language processing (NLP) application with options to measure sentiment, detect entities, semantic roles, and other concepts.N/A
    Pricing
    Azure Machine LearningIBM Watson Discovery
    Editions & Modules
    Studio Pricing - Free
    $0.00
    per month
    Production Web API - Dev/Test
    $0.00
    per month
    Studio Pricing - Standard
    $9.99
    per ML studio workspace/per month
    Production Web API - Standard S1
    $100.13
    per month
    Production Web API - Standard S2
    $1000.06
    per month
    Production Web API - Standard S3
    $9999.98
    per month
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure Machine LearningIBM Watson Discovery
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Azure Machine LearningIBM Watson Discovery
    Considered Both Products
    Microsoft
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    81%
    Would buy again
    21 Answers
    Delivers good value for the price
    No answers on this topic
    74%
    Delivers good value for the price
    14 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    26 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    18 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    23 Answers
    Best Alternatives
    Azure Machine LearningIBM Watson Discovery
    Small Businesses
    TensorFlow
    Score7.6 out of 10
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    Score8.5 out of 10
    Medium-sized Companies
    Google Cloud AI
    Score8.7 out of 10
    Elasticsearch
    Score8.5 out of 10
    Enterprises
    Google Cloud AI
    Score8.7 out of 10
    Amazon CloudSearch
    Score8.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure Machine LearningIBM Watson Discovery
    Likelihood to Recommend
    6.0
    (5 ratings)
    8.3
    (26 ratings)
    Likelihood to Renew
    7.0
    (1 ratings)
    9.1
    (2 ratings)
    Usability
    7.0
    (2 ratings)
    4.8
    (3 ratings)
    Support Rating
    7.9
    (2 ratings)
    10.0
    (2 ratings)
    Implementation Rating
    8.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Azure Machine LearningIBM Watson Discovery
    Likelihood to Recommend
    Microsoft
    I would highly recommend Azure machine learning design for those with less access to high-end computing infrastructure, as using Azure saves a lot of time, money, and effort by providing a hustle-free platform that is easy to use and train your employees on. On the other hand, if you are looking for complete control of the machine learning model you create and would like to add detailed functionalities and try different algorithms, then Azure is less suitable here as it’s very high level.
    Incentivized
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    IBM
    Overall, IBM Watson Discovery is an amazing technology that we use with our clients to address various business problems, but the biggest challenge has always been about ingesting, analyzing, enriching, and searching huge collections of documents and allowing our end users and SMEs to be able to search for what they need to reduce the time and efforts spent daily on a manual search through various collections of documents. We have successfully managed to reduce manual work by over 80%, and now our SMEs are being used for the skills they have to gather insights rather than do manual work.
    Incentivized
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    Pros
    Microsoft
    • Easy to create the experiment.
    • Easy to adopt the best algorithm.
    • Efficient way to deploy the model as a web service.
    • Centralized platform for the life cycle of machine learning goal.
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    IBM
    • It is an excellently fast platform with documents and the answers to queries.
    • With automation learning beneficial as it saves time.
    • When searching for a document, everything stays located and easy to find.
    • Acceptance of various documents.
    • It has a quite comfortable Technical support, always available when required.
    Incentivized
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    Cons
    Microsoft
    • Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
    • Tableau interface: last time I checked there was no easy way to connect with Tableau.
    • Cloud based: You always need a good internet connection to use it.
    Incentivized
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    IBM
    • I believe AI should be more flexible about providing data. However, it's understandable that you need to provide the details you need in a more specific and detailed way.
    • The interface could use more tweaking. Being new to the program, it was kind of hard to navigate.
    • Luckily, there was a customized feature of the dashboard that I could set up, and having something that you know where you are placed always feels familiar and comfortable.
    Incentivized
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    Usability
    Microsoft
    Good UX/UI and overall good usability, but it takes a while to get used to the product & platform. The whole design seems fragmented with little in terms of integration with project management tools such as JIRA, or wireframing. Overall it feels like an unfinished product that's meant for teaching more than for production.
    Incentivized
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    IBM
    IBM Watson Discovery has the best user capabilities and easily transform business decision-making portfolio. The automation system saves time used in data analysis as opposed to manual research that consumes a lot of time. The visualization across the dashboard enables my team to interpret complex data and use it to make reliable marketing decisions.
    Incentivized
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    Support Rating
    Microsoft
    I'm satisfied with the Azure Machine Learning Studio- it fulfilled my goal in a single channel. Even haven't worr[ied] about the maintenance or any fault tolerance. This provide[s] the user interactive UI to grab the features easily. [Their] support teams also very help[ful], they stand with us at any time.
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    IBM
    Similar to all IBM Watson and Salesforce product solutions, the overall support would be a 10/10. Their provided FAQ's help with frequently experienced issues and if still unable to figure something out, their customer service representatives are always super responsive. With instant chat functions available, it is easy to ask a quick question rather than sitting on hold.
    Incentivized
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    Implementation Rating
    Microsoft
    Not sure
    Read full review
    IBM
    No answers on this topic
    Alternatives Considered
    Microsoft
    It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.
    Incentivized
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    IBM
    Discovery differs from its competitors due to the better ease of implementation and the high level of natural language recognition, it is equal in integration resources such as API and workflow or process pipeline, but it loses in the price for a high volume of documents and/or research. If you own or plan to use other services from the IBM Watson family, there is no doubt that Watson discovery is your best option. Another important point is if you plan to use a cloud or on-premise service (local server or private cloud).
    Incentivized
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    Return on Investment
    Microsoft
    • Reduce energy consumption caused by GPUs.
    • Saves on recycling and transporting costs and maintenance caused by buying high-end equipment.
    • Improve productivity as building products using Azure is easier than building everything up from scratch (e.g., machine learning and AI applications).
    Incentivized
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    IBM
    • We find its Enterprise plan expensive for a country of LATAM. For US or Europe based businesses, looks great.
    • A Big Data and massive queries based company would find the service expensive. Maybe a flat price plan would be helpful.
    • Have you thought in making a cheaper plan where you take the learning from your customer's data to enrich your AI tool?
    Incentivized
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    ScreenShots