Software Alternatives, Accelerators & Startups

Deploifai VS Evidently AI

Compare Deploifai VS Evidently AI and see what are their differences

Deploifai logo Deploifai

Software platform for deploying AI models and ML training

Evidently AI logo Evidently AI

Open-source monitoring for machine learning models
  • Deploifai Landing page
    Landing page //
    2023-08-22
  • Evidently AI Landing page
    Landing page //
    2023-08-19

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Evidently AI videos

How to Monitor Machine Learning Models (Evidently AI)

Category Popularity

0-100% (relative to Deploifai and Evidently AI)
AI
29 29%
71% 71
Developer Tools
23 23%
77% 77
Open Source
100 100%
0% 0
Data Science And Machine Learning

User comments

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Social recommendations and mentions

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

Deploifai mentions (1)

  • Ask HN: What ML platform are you using?
    I have been building Deploifai for a year. I built it for myself early on because I wanted to train machine learning models on the cloud since we don't have the resources for a physical machine. I basically wanted to use my AWS account to create VMs with environments pre-configured, and just simply start building my ML models. Deploifai sets up the VM with pre-selected ML framework, NVIDIA drivers and Jupyterlab.... - Source: Hacker News / over 2 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 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 2 years ago

What are some alternatives?

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iko.ai - Real-time collaborative notebooks on your own Kubernetes clusters to train, track, package, deploy, and monitor your machine learning models.