Evidently AI
ML Showcase
Censius.ai
iko.ai
ML5.js
Lobe
Amazon Machine Learning
Machine Learning Playground
Akkio
Algforce.ai
Lobe
Machine Learning Playground
Amazon Machine Learning
Spell
Microsoft Power BI
Obviously.ai
Evidently AI AkkioBased on our record, Evidently AI should be more popular than Akkio. 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.
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
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
This is very cool! Thanks for sharing. Akkio (disclaimer: associated with the tool) also released a similar feature, where you can type in your prompt and the datasets (whether it's a csv import, Google Sheet integration, or one of the other db options) will update accordingly. It removes the need for SQL entirely. Microsoft BI now includes advanced no-code queries, Google Analytics 4 answers question in... Source: over 1 year ago
ML Showcase - A curated collection of machine learning projects
Algforce.ai - Natural language data query, AI data insight, and data collaborative construction. Integration services for office software and internal application embeddings are coming soon.
Censius.ai - Building the future of MLOps
Lobe - Visual tool for building custom deep learning models
iko.ai - Real-time collaborative notebooks on your own Kubernetes clusters to train, track, package, deploy, and monitor your machine learning models.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
