Software Alternatives, Accelerators & Startups

Evidently AI VS ML5.js

Compare Evidently AI VS ML5.js and see what are their differences

Evidently AI logo Evidently AI

Open-source monitoring for machine learning models

ML5.js logo ML5.js

Friendly machine learning for the web
  • Evidently AI Landing page
    Landing page //
    2023-08-19
  • ML5.js Landing page
    Landing page //
    2021-10-12

Evidently AI features and specs

  • Automated Monitoring
    Evidently AI provides automated monitoring of machine learning models, which helps in identifying performance degradation or drift, ensuring models remain accurate and reliable over time.
  • User-Friendly Interface
    The platform offers a user-friendly interface that allows practitioners with varying levels of expertise to easily navigate through features and monitor models effectively.
  • Comprehensive Reporting
    Evidently AI generates detailed reports that include key metrics and insights about model performance, making it easier to communicate findings with stakeholders.
  • Integration Capabilities
    It can be integrated seamlessly with existing data pipelines and machine learning infrastructures, allowing for more streamlined workflows.
  • Open Source
    As an open-source tool, Evidently AI enables greater flexibility and customization, allowing users to modify and extend its features to suit specific needs.

Possible disadvantages of Evidently AI

  • Limited Advanced Features
    While Evidently AI covers basic and intermediate monitoring needs well, it may lack some of the more advanced features offered by other specialized commercial platforms.
  • Dependency Management
    Being open-source, managing dependencies and ensuring compatibility with other tools or libraries can sometimes be challenging and may require additional effort.
  • Resource Intensive
    The tool may require significant computational resources for large scale models or big datasets, which could be a limitation for some users.
  • Initial Setup Complexity
    Initial setup and configuration of the platform might be complex for users without a strong technical background, potentially causing a steeper learning curve.

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.

Evidently AI videos

How to Monitor Machine Learning Models (Evidently AI)

ML5.js videos

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

Category Popularity

0-100% (relative to Evidently AI and ML5.js)
AI
43 43%
57% 57
Developer Tools
43 43%
57% 57
Data Science And Machine Learning
Open Source
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, ML5.js should be more popular than Evidently AI. 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.

Evidently AI mentions (2)

  • [D] Using MLFlow for model performance tracking
    It is doable. However the main focus of MLFlow is in experiment tracking. I would suggest for you to look into another monitoring tools such evidentlyai . You can track more things than performance (e.g.data drift). Which may be helpful in a production setting. Source: over 2 years ago
  • Five Data Quality Tools You Should Know
    Evidently is an open-source Python library that analyzes and monitors machine learning models. It generates interactive reports based on Panda DataFrames and CSV files for troubleshooting models and checking data integrity. These reports show model health, data drift, target drift, data integrity, feature analysis, and performance by segment. - Source: dev.to / over 3 years ago

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 / 12 days 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: about 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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What are some alternatives?

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

ML Showcase - A curated collection of machine learning projects

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

Pretrained AI - Integrate pretrained machine learning models in minutes.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

Censius.ai - Building the future of MLOps

Apple Machine Learning Journal - A blog written by Apple engineers