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ML5.js VS Monitor ML

Compare ML5.js VS Monitor ML and see what are their differences

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ML5.js logo ML5.js

Friendly machine learning for the web

Monitor ML logo Monitor ML

Real-time production monitoring of ML models, made simple.
  • ML5.js Landing page
    Landing page //
    2021-10-12
  • Monitor ML Landing page
    Landing page //
    2021-10-12

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.

Monitor ML features and specs

  • Comprehensive Monitoring
    Monitor ML offers a wide range of monitoring features that can track various metrics and performance indicators of machine learning models, helping users identify and address potential issues quickly.
  • User-Friendly Interface
    The platform is designed with an intuitive user interface, making it accessible for users with varying levels of technical expertise to navigate and utilize effectively.
  • Automated Alerts
    Monitor ML provides automated alert systems that notify users of anomalies or significant changes in model performance, allowing for proactive management and intervention.
  • Scalability
    The service is scalable, meaning that it can accommodate the needs of both small-scale and large-scale machine learning projects, making it a versatile option for different business sizes.
  • Integration Capabilities
    Monitor ML easily integrates with popular machine learning frameworks and tools, facilitating seamless implementation into existing workflows and systems.

Possible disadvantages of Monitor ML

  • Cost
    Depending on the features and scale, Monitor ML can be expensive, potentially making it less accessible for smaller companies or projects with limited budgets.
  • Complex Configuration
    While the interface is user-friendly, setting up and configuring the monitoring system to fit specific needs can be complex and time-consuming for inexperienced users.
  • Limited Customization
    Some users might find the customization options limited, especially for highly specific monitoring needs that may not be fully supported by the platform's existing features.
  • Data Privacy Concerns
    As with many third-party platforms, there may be concerns about data privacy and security, particularly when dealing with sensitive or proprietary data.
  • Dependency on External Service
    Relying on an external service for monitoring can lead to potential issues if the service experiences downtime or technical difficulties.

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

Monitor ML videos

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Category Popularity

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

ML5.js

Monitor ML

AI
64 64%
AI
36% 36
Developer Tools
59 59%
Developer Tools
41% 41
Data Science And Machine Learning
70 70%
Data Science And Machine Learning
30% 30
Tech
49 49%
Tech
51% 51

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
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Monitor ML mentions (0)

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

What are some alternatives?

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

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

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

TensorFlow Lite - Low-latency inference of on-device ML models

Apple Machine Learning Journal - A blog written by Apple engineers

Spell - Deep Learning and AI accessible to everyone

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