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ML5.js VS Async

Compare ML5.js VS Async and see what are their differences

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ML5.js logo ML5.js

Friendly machine learning for the web

Async logo Async

Async is a one-of-a-kind communication and project management tool for small teams of software engineers.
  • ML5.js Landing page
    Landing page //
    2021-10-12
  • Async Landing page
    Landing page //
    2022-10-11

ML5.js features and specs

  • Ease of Use
    ml5.js is designed with simplicity in mind, making machine learning accessible to artists, creative coders, and students, even those without a robust background in AI or machine learning.
  • Browser-based
    Operates directly in the browser, eliminating the need for any additional setup or dependencies, which makes it highly compatible with web projects.
  • Pre-trained Models
    Includes a variety of pre-trained models for quick implementation of complex machine learning tasks like image classification, pose detection, and text generation.
  • Community and Documentation
    Strong community support and well-documented guides and examples help new users get started quickly and find solutions to common issues.
  • Integration with p5.js
    Integrates seamlessly with p5.js, a popular JavaScript library for creative coding, facilitating the development of interactive and visually engaging applications.

Possible disadvantages of ML5.js

  • Performance Limitations
    Since it runs in the browser, it may not be suitable for performance-intensive applications or those requiring real-time processing of large datasets.
  • Limited Customization
    While it offers pre-trained models, there is limited functionality for training new models from scratch compared to more comprehensive libraries like TensorFlow.js.
  • Dependency on Web Standards
    Depends on the performance and capabilities of the client's browser, which can vary significantly between different users and devices.
  • Size of Models
    Some pre-trained models can be quite large, which may affect loading times and performance on slower network connections or less powerful devices.
  • Scope
    Focused on high-level tasks and applications, which might not be sufficient for advanced machine learning requirements or niche functionalities outside its provided models.

Async features and specs

  • Efficiency
    Async allows for non-blocking operations, which can lead to more efficient code execution as tasks can run concurrently without waiting for others to complete.
  • Scalability
    By handling multiple tasks simultaneously, async allows applications to scale more easily, accommodating more users and data without significant performance loss.
  • Improved Responsiveness
    Applications using async can remain responsive even when dealing with long-running operations, enhancing the user experience by not freezing or lagging.
  • Resource Optimization
    Async operations can utilize resources more effectively, reducing idle time for CPU and I/O operations which leads to better overall system performance.

Possible disadvantages of Async

  • Complexity
    Writing and debugging async code can be more complex compared to synchronous code due to the need to manage callbacks and handle potential concurrency issues.
  • Error Handling
    Errors in async operations can be harder to handle and trace, as they might not propagate in the same way as they do in synchronous code, requiring additional effort to manage.
  • Readability
    Async code can sometimes be harder to read and understand, particularly for developers who are not familiar with this programming paradigm, potentially increasing code maintenance challenges.
  • Compatibility
    Not all environments and libraries fully support async operations, which might limit its usage or require additional workarounds or polyfills.

Analysis of ML5.js

Overall verdict

  • ML5.js is considered a good tool for web developers who want to incorporate machine learning into their projects without needing extensive knowledge of the underlying algorithms. It's particularly noted for its simplicity and ease of use.

Why this product is good

  • ML5.js is a high-level JavaScript library built on top of TensorFlow.js. It is designed to make machine learning accessible to web developers with minimal expertise in machine learning or deep learning. The library provides easy-to-use functions for tasks such as image and video classification, pose detection, text generation, and more. Its simplicity and ease of integration make it ideal for rapid prototyping and educational purposes.

Recommended for

    ML5.js is recommended for educators, beginners, artists, and developers who want to quickly implement machine learning models in web applications. It is also suitable for creative coding projects and interactive applications where simplicity and ease of use are important.

ML5.js videos

+ Add

ml5.js: Train Your Own Neural Network

More videos:

  • Review - ml5.js: Image Classification with MobileNet
  • Review - Image classification to gif with ML5.js | Vue.js Virtual Meetup

Async videos

+ Add

Sakamoto Ryuichi - async (Album Review)

More videos:

  • Review - Workflow From Home: Ep 11 - Async Review
  • Review - Ryuichi Sakamoto - async - album preview

Category Popularity

0-100% (relative to ML5.js and Async)

ML5.js

Async

AI
100 100%
AI
0% 0
Project Management
0 0%
Project Management
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Work Management
0 0%
Work Management
100% 100

User comments

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Social recommendations and mentions

Based on our record, ML5.js seems to be more popular. It has been mentiond 10 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.

ML5.js mentions (10)

  • How AI is Transforming Front-End Development in 2025!
    Ml5.js: Built on top of TensorFlow.js, it provides a user-friendly interface for implementing machine learning in web applications.​. - Source: dev.to / about 2 months ago
  • Riffr - Create Photo Montages in the Browser with some ML Magic✨
    Important APIs - ml5 for in-browser detection, face-api that uses tensorflow-node to accelerate on-server detection. VueUse for a bunch of useful component tools like the QR Code generator. Yahoo's Gifshot for creating gif files in-browser etc. - Source: dev.to / over 2 years ago
  • Brain.js: GPU Accelerated Neural Networks in JavaScript
    See also: https://ml5js.org/ "The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.". - Source: Hacker News / almost 3 years ago
  • [Showoff Saturday] I made a captcha prototype that requires a banana
    I used ml5js.org , p5js.org and https://teachablemachine.withgoogle.com to train the Banana images. When you create a new image project on Teachable Machine, you can output the p5js and basically use it right out of the box - I customized js, css, and html from there. Source: over 3 years ago
  • My First 30 Days of 100 Days of Code.
    Going forward: I'll be 100% into JavaScript. You can use JavaScript in so many fields nowadays. Websites React, Mobile Apps React Native, Machine Learning TensorFlow & ML5, Desktop Applications Electron, and of course the backend Node as well. It's kind of a no-brainer. Of course, they all have specific languages that are better, but for now, JavaScript is a bit of a catch-all. - Source: dev.to / over 3 years ago
View more

Async mentions (0)

We have not tracked any mentions of Async yet. Tracking of Async recommendations started around Mar 2021.

What are some alternatives?

When comparing ML5.js and Async, you can also consider the following products

Amazon Machine Learning - Machine learning made easy for developers of any skill level

Unfuddle - Unfuddle is a secure, hosted project management solution for software development teams.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

Insou AI - Make everyone love speech

Apple Machine Learning Journal - A blog written by Apple engineers

Embold.io - Peer Code Review

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