AETROS VS Evidently AI

AETROS

Create, train and monitor deep neural networks

Evidently AI

Open-source monitoring for machine learning models

Landing page //
2023-07-18

Landing page //
2023-08-19

Evidently AI

Website: evidentlyai.com

Edit details

AETROS features and specs

User-Friendly Interface
AETROS DeepKit offers an intuitive and easy-to-navigate interface, making it accessible for both beginners and experienced users in machine learning.
Comprehensive Experiment Management
The platform provides robust tools for tracking, comparing, and managing machine learning experiments, which can help in streamlining the workflow and improving productivity.
Collaboration Features
It allows teams to collaborate effectively by sharing insights and results within the platform, facilitating smoother collaboration among team members.
Integration Capabilities
AETROS DeepKit can be integrated with other tools and platforms, which helps in leveraging existing workflows and datasets without requiring major changes.
Scalability
The platform is designed to scale efficiently with the user's needs, making it suitable for both small projects and large enterprise-level AI initiatives.

Possible disadvantages of AETROS

Cost
The platform may have a significant cost, especially for startups or individual developers who might be operating on a limited budget.
Learning Curve
Despite its user-friendly design, there might still be a learning curve involved, especially for those who are new to machine learning experiment management tools.
Dependency on Cloud
AETROS DeepKit relies heavily on cloud infrastructure, which may not be suitable for organizations with strict data residency regulations or those preferring on-premise solutions.
Performance Limitations
In certain circumstances, users may encounter performance limitations, particularly when managing extremely large datasets or a vast number of concurrent experiments.
Limited Customization
Some users may find that the platform offers limited customization options, restricting their ability to tailor the tool to specific workflows or requirements.

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.

Analysis of Evidently AI

Overall verdict

Yes, Evidently AI is a solid choice for monitoring and understanding machine learning models.

Why this product is good

User-Friendly: Evidently AI offers an intuitive interface that simplifies the process of monitoring machine learning models.
Comprehensive Dashboards: It provides detailed dashboards that help in tracking and understanding model performance over time.
Open-Source: As an open-source tool, it allows users to customize and extend its functionality, ensuring it meets specific needs.
Automated Reporting: The platform automates the creation of reports, saving time and reducing manual effort in analyzing model outputs.
Community Support: Being open-source, it has a community that contributes to its growth and provides support, making it reliable and up-to-date.

Recommended for

Data Scientists: To streamline model monitoring and gain insights into model performance.
Machine Learning Engineers: To automate the reporting and monitoring process, ensuring models perform optimally.
Organizations: That need a scalable and customizable solution for machine learning model reporting and monitoring.
Companies Looking for Open-Source Solutions: Those who prefer open-source tools for flexibility and cost-effectiveness.

AETROS videos

No AETROS videos yet. You could help us improve this page by suggesting one.

Add video

Evidently AI videos

+ Add

How to Monitor Machine Learning Models (Evidently AI)

Category Popularity

0-100% (relative to AETROS and Evidently AI)

Evidently AI

23 23%

77% 77

Developer Tools

21 21%

Developer Tools

79% 79

Games

100 100%

Games

0% 0

Data Science And Machine Learning

0 0%

Data Science And Machine Learning

100% 100

User comments

Share your experience with using AETROS and Evidently AI. For example, how are they different and which one is better?

Social recommendations and mentions

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

AETROS mentions (1)

Introducing Deepkit ORM, a high performance ORM for TypeScript
Deepkit ORM is one of a whole collection of high performance libraries written in the last years for my need in developing complex isomorphic TypeScript applications (like for example https://deepkit.ai). Since we approach the beta version I'd like to introduce you to one of its flagship libraries, the ORM, and collect feedback. So, if you are interested, please keep reading and drop me a comment about your thoughts! Source: almost 4 years ago

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: almost 3 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