A collaborative review and approval application that keeps everyone on the same page. ReviewStudio is the easiest way to track feedback, tasks, revisions and approvals.
It's great for getting projects delivered faster:
*Markup and comment on images, video, PDF and web pages from any device *See the status of all your reviews in individual dashboards *Keep track of changes with side-by-side comparisons
It's collaborative and centralized:
*Need to give someone a shoutout? No problem. Do it with @Mentions *Use attachments to add reference files to any comments *Bring your teams and clients together with collaborative discussion threads *Turn on presentation mode to review and collaborate on projects *Sync in real time with any number of participants *Review your projects independently or collaboratively in live reviews
It's about excellent support - and making your work look good:
*Customize the online proofing experience with your own branded review site hosted on your own subdomain. *Deploy a private, branded review site with custom domain for managing all reviews and users. *99.99% uptime with 24/7 monitoring and response team *100% SSL encryption and security layer validated by HITRUST APIs and SSO options to support integration with any existing software or services Direct email and phone support
Based on our record, Apache Airflow seems to be more popular. It has been mentiond 67 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.
An integral part of an ML project is data acquisition and data transformation into the required format. This involves creating ETL (extract, transform, load) pipelines and running them periodically. Airflow is an open source platform that helps engineers create and manage complex data pipelines. Furthermore, the support for Python programming language makes it easy for ML teams to adopt Airflow. - Source: dev.to / 8 days ago
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / about 1 month ago
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 4 months ago
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 7 months ago
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 7 months ago
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