Based on our record, tl;dv should be more popular than Evidently AI. It has been mentiond 6 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.
Tldv.io: An AI-powered tool that can take notes of your meetings and even whip up summaries. Source: about 1 year ago
I've found Otter.ai or Fathom for zoom meeting recording and summaries better than tldv.io or tactiq. Source: about 1 year ago
I use https://tldv.io to organize all the interviews in one folder. You get summaries, transcription, and the video. Most of the core features are free to use. Source: about 1 year ago
Why don't you just use tldv? https://tldv.io/ It does exactly that. Source: almost 2 years ago
Https://tldv.io/ I don’t think this works with Teams though. Source: about 2 years 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: 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
Fireflies.ai for Meetings - Record, transcribe and search your calls
ML Showcase - A curated collection of machine learning projects
Otter.ai - Your AI meeting assistant that takes live notes and generates summaries and other insights using Meeting GenAI.
Censius.ai - Building the future of MLOps
Tactiq - Meeting notes powered by speech to text transcription
iko.ai - Real-time collaborative notebooks on your own Kubernetes clusters to train, track, package, deploy, and monitor your machine learning models.