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BigML VS AWS IoT Device Management

Compare BigML VS AWS IoT Device Management and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

BigML logo BigML

BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

AWS IoT Device Management logo AWS IoT Device Management

Onboard, organize, monitor, and remotely manage connected devices at scale
  • BigML Landing page
    Landing page //
    2022-10-08
  • AWS IoT Device Management Landing page
    Landing page //
    2023-05-02

BigML features and specs

  • User-Friendly Interface
    BigML offers an intuitive web-based interface that makes it easy for users to build and deploy machine learning models without deep technical knowledge.
  • Wide Range of Algorithms
    It supports various machine learning algorithms, including regression, classification, clustering, and anomaly detection, catering to diverse use cases.
  • Ease of Integration
    BigML provides robust API support, allowing seamless integration with other applications and systems for streamlined workflows.
  • Visualization Tools
    The platform includes powerful visualization tools that help in understanding data, model performance, and results, aiding in better decision-making.
  • Scalability
    BigML's cloud-based infrastructure allows it to scale easily, handling large datasets and complex models efficiently.
  • Automated Workflows
    It offers automation features like WhizzML for creating automated workflows and advanced scripts, making repetitive tasks simpler.

Possible disadvantages of BigML

  • Cost
    The pricing structure can be a limiting factor for startups or individual users, especially when dealing with large amounts of data.
  • Limited Customization
    While the platform offers many pre-built algorithms, there is limited scope for customization compared to building models from scratch using open-source libraries.
  • Learning Curve
    Despite its user-friendly design, there can be a learning curve for those unfamiliar with machine learning concepts, particularly for advanced features.
  • Dependency on Internet
    As a cloud-based service, users need a reliable internet connection to access and utilize BigML's features, which can be a drawback in areas with poor connectivity.
  • Data Privacy Concerns
    Using a cloud-based service can raise data privacy and security concerns, particularly for sensitive or proprietary data.

AWS IoT Device Management features and specs

No features have been listed yet.

Analysis of BigML

Overall verdict

  • BigML is a good choice for users seeking an accessible and efficient machine learning platform. Its combination of ease of use, flexibility, and robust features allows for effective data analysis and model deployment, making it suitable for many use cases.

Why this product is good

  • BigML is a popular machine learning platform known for its user-friendly interface and comprehensive suite of tools that cater to both beginners and experts. It offers a wide range of machine learning models and allows for seamless integration with other tools and workflows. Users appreciate its ease of use, scalability, and ability to handle various types of data. Additionally, BigML provides extensive documentation and support, making it an attractive option for those looking to implement machine learning solutions without extensive coding knowledge.

Recommended for

  • Data scientists and analysts looking for an intuitive platform to build and deploy models.
  • Businesses aiming to integrate machine learning into their operations without a steep learning curve.
  • Educators and students who wish to explore machine learning concepts hands-on.
  • Developers needing a scalable solution with ample API support for custom applications.
  • Organizations looking for a reliable and secure cloud-based machine learning solution.

BigML videos

+ Add

BigML is Machine Learning for Everyone

More videos:

  • Review - BigML Spring 2016 Webinar - WhizzML!

AWS IoT Device Management videos

+ Add

AWS Tutorials - Using Jobs in AWS IoT Device Management

Category Popularity

0-100% (relative to BigML and AWS IoT Device Management)

BigML

AWS IoT Device Management

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
IoT Platform
0 0%
IoT Platform
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Testing
0 0%
Testing
100% 100

User comments

Share your experience with using BigML and AWS IoT Device Management. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, BigML seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

BigML mentions (2)

  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Bigml.com — Hosted machine learning algorithms. Unlimited free tasks for development, limit of 16 MB data/task. - Source: dev.to / almost 4 years ago
  • Theory: The price action was intentionally manipulated to prevent any AI from being able to predict it. First time this model shows as flat. Forever.
    They know the website is bigml.com it's possible they have many magnitudes better algorithms to predict this shit. And it's also possible they paid some quants to come up with price action that just completely fucks with BigML's algorithm entirely to make it look flat. Source: about 4 years ago

AWS IoT Device Management mentions (0)

We have not tracked any mentions of AWS IoT Device Management yet. Tracking of AWS IoT Device Management recommendations started around Mar 2021.

What are some alternatives?

When comparing BigML and AWS IoT Device Management, you can also consider the following products

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

SocketXP - Raspberry Pi and IoT device remote access, monitoring, control and management at scale.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Azure IoT Hub - Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

ngrok - ngrok enables secure introspectable tunnels to localhost webhook development tool and debugging tool.

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