Software Alternatives, Accelerators & Startups

BigML VS Plotly

Compare BigML VS Plotly and see what are their differences

BigML logo BigML

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

Plotly logo Plotly

Low-Code Data Apps
  • BigML Landing page
    Landing page //
    2022-10-08
  • Plotly Landing page
    Landing page //
    2023-07-31

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.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

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.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

BigML videos

BigML is Machine Learning for Everyone

More videos:

  • Review - BigML Spring 2016 Webinar - WhizzML!

Plotly videos

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to BigML and Plotly)
Data Science And Machine Learning
Data Visualization
0 0%
100% 100
Technical Computing
100 100%
0% 0
Charting Libraries
0 0%
100% 100

User comments

Share your experience with using BigML and Plotly. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare BigML and Plotly

BigML Reviews

We have no reviews of BigML yet.
Be the first one to post

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than BigML. While we know about 34 links to Plotly, we've tracked only 2 mentions of BigML. 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 / about 5 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: over 5 years ago

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / almost 2 years ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing BigML and Plotly, 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.

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

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

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

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

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.