Papers with Code
ML5.js
Amazon Machine Learning
Machine Learning Playground
Lobe
arXiv
mlblocks
Spell
Evidently AI
ML5.js
ML Showcase
Lobe
Pretrained AI
Censius.ai
Lightly AI
Vast.ai
Papers with CodeBased on our record, Papers with Code seems to be a lot more popular than Evidently AI. While we know about 96 links to Papers with Code, we've tracked only 2 mentions of Evidently AI. 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.
Papers With Code is one of the good resources to get you to get started. - Source: dev.to / 17 days ago
For ML/DL papers you can check https://paperswithcode.com/. - Source: Hacker News / 4 months ago
This resource has been invaluable to me: https://paperswithcode.com/ From the past examples you give it sounds like you were into computer vision. There’s been a ton of developments since then, and I think you’d really enjoy the applications of some of those classic convolutional and variational encoder techniques in combination with transformers. A state of the art multimodal non-autoregressive neural net model... - Source: Hacker News / 5 months ago
And also you can find papers with their implementations in code here: http://paperswithcode.com. - Source: Hacker News / 5 months ago
Check out paperswithcode, scroll through arxiv, or browse some well-known conferences in the field (NeurIPS, ICML). Source: 5 months ago
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 1 year 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
ML5.js - Friendly machine learning for the web
Amazon Machine Learning - Machine learning made easy for developers of any skill level
ML Showcase - A curated collection of machine learning projects
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Lobe - Visual tool for building custom deep learning models
Pretrained AI - Integrate pretrained machine learning models in minutes.
