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Darwin vs Microsoft Azure Machine Learning Studio comparison

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Quotes From Members
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Here are some excerpts of what they said:
Pros
"The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science."

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"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.""It's good for citizen data scientists, but also, other people can use Python or .NET code.""The solution is very fast and simple for a data science solution.""The solution is very easy to use, so far as our data scientists are concerned.""The UI is very user-friendly and that AI is easy to use.""The initial setup is very simple and straightforward.""The interface is very intuitive.""The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."

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Cons
"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."

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"I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else.""They should have a desktop version to work on the platform.""The data preparation capabilities need to be improved.""In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data.""There should be data access security, a role level security. Right now, they don't offer this.""It would be nice if the product offered more accessibility in general.""The interface is a bit overloaded.""The solution should be more customizable. There should be more algorithms."

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Pricing and Cost Advice
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  • "The licensing cost is very cheap. It's less than $50 a month."
  • "There is a license required for this solution."
  • "I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
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    Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
    Top Answer: 
    The initial setup is very simple and straightforward.
    Top Answer: 
    The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
    Ranking
    13th
    Views
    649
    Comparisons
    220
    Reviews
    1
    Average Words per Review
    3,064
    Rating
    10.0
    4th
    Views
    16,529
    Comparisons
    13,221
    Reviews
    14
    Average Words per Review
    484
    Rating
    7.7
    Comparisons
    Also Known As
    Azure Machine Learning, MS Azure Machine Learning Studio
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    Overview

    SparkCognition builds leading artificial intelligence solutions to advance the most important interests of society. We help customers analyze complex data, empower decision making, and transform human and industrial productivity with award-winning machine learning technology and expert teams focused on defense, IIoT, and finance.

    Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

    It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.

    Microsoft Azure Machine Learning Will Help You:

    • Rapidly build and train models
    • Operationalize at scale
    • Deliver responsible solutions
    • Innovate on a more secure hybrid platform

    With Microsoft Azure Machine Learning You Can:

    • Prepare data: Microsoft Azure Machine Learning Studio offers data labeling, data preparation, and datasets.
    • Build and train models: Includes notebooks, Visual Studio Code and Github, Automated ML, Compute instance, a drag-and-drop designer, open-source libraries and frameworks, customizable dashboards, and experiments
    • Validate and deploy: Manage endpoints, automate machine learning workflows (pipeline CI/CD), optimize models, access pre-built container images, share and track models and data, train and deploy models across multi-cloud and on-premises.
    • Manage and monitor: Track, log, and analyze data, models, and resources; Detect drift and maintain model accuracy; Trace ML artifacts for compliance; Apply quota management and automatic shutdown; Leverage built-in and custom policies for compliance management; Utilize continuous monitoring with Azure Security Center.

    Microsoft Azure Machine Learning Features:

    • Easy & flexible building interface: Execute your machine learning development through the Microsoft Azure Machine Learning Studio using drag-and-drop components that minimize the code development and straightforward configuration of properties. By being so flexible, the solution also helps build, test ,and generate advanced analytics based on the data.
    • Wide range of supported algorithms: Configuration is simple and easy because Microsoft Azure ML offers readily available well-known algorithms. There is also no limit in importing training data, and the solution enables you to fine-tune your data easily, saving money and time and helping you generate more revenue.
    • Easy implementation of web services: Simply drag and drop your data sets and algorithms, and link them together to implement web services. It only requires one click to create and publish the web service, which can be used from any device by passing valid credentials.
    • Great documentation: Microsoft Azure provides full stacks of documentation, such as tutorials, quick starts, references, and many other resources that help you understand how to easily build, manage, deploy, and access machine learning solutions effectively.

    Microsoft Azure Machine Learning Benefits:

    • It is fully integrated with Python and R SDKs.
    • It has an updated drag-and-drop interface, generally known as Azure Machine Learning Designer.
    • It supports MLPipelines, where you can build flexible and modular pipelines to automate workflows.
    • It supports multiple model formats depending upon the job type.
    • It has automated model training and hyperparameter tuning with code-first and no-code options.
    • It supports data labeling projects.

    Reviews from Real Users:

    "The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates

    "The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company

    "The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company

    "The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company

    Offer
    Learn more about Darwin
    Learn more about Microsoft Azure Machine Learning Studio
    Sample Customers
    Hunt Oil, Hitachi High-Tech Solutions
    Walgreens Boots Alliance, Schneider Electric, BP
    Top Industries
    VISITORS READING REVIEWS
    Comms Service Provider26%
    Manufacturing Company14%
    Computer Software Company11%
    Financial Services Firm8%
    REVIEWERS
    Financial Services Firm14%
    Recruiting/Hr Firm14%
    Computer Software Company14%
    Energy/Utilities Company14%
    VISITORS READING REVIEWS
    Computer Software Company24%
    Comms Service Provider19%
    Energy/Utilities Company6%
    Manufacturing Company6%
    Company Size
    REVIEWERS
    Small Business75%
    Large Enterprise25%
    REVIEWERS
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: January 2022.
    563,208 professionals have used our research since 2012.

    Darwin is ranked 13th in Data Science Platforms with 1 review while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 16 reviews. Darwin is rated 10.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Darwin writes "Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has the ability to do templating and transfer it so that we can do multiple types of models and data mining". Darwin is most compared with H2O.ai and IBM Watson Studio, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Dataiku Data Science Studio, IBM Watson Studio, KNIME and Alteryx.

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