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Qualdo.ai is a leader in monitoring and improving data quality and ML-Models for enterprises adopting a multi-cloud and modern data ecosystem. Qualdo.ai is a proprietary SaaS product where Data-Quality meets Model Monitoring.
Available on Azure, AWS and Google cloud databases, Qualdo™ helps enterprises monitor mission-critical ML & data issues, errors, and quality using Augmented Data Engineering. In other words, performance is measured and monitored in autopilot mode.
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Based on our record, GitHub seems to be more popular. It has been mentiond 2466 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.
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / 1 day ago
Import requests From bs4 import BeautifulSoup From datetime import datetime Def fetch_github_trending(): url = "https://github.com/trending?since=daily" response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') repos = [] for article in soup.select('article.Box-row'): repo_link = article.select_one('h2 a')['href'] stars_today =... - Source: dev.to / 2 days ago
Git clone https://github.com//.git /opt/app Cd /opt/app Docker build -t app . Docker run -d --name app --restart unless-stopped -p 8080:8080 app. - Source: dev.to / 5 days ago
The core of the ecosystem is the official open-source server hosted on GitHub. It is written in TypeScript and implements the full MCP specification. - Source: dev.to / 10 days ago
This is why the gate needs a trace it can trust, and why AgentLens is the other half of this workflow. agent-eval scores and gates the output; AgentLens captures the trace of how the agent got there — every model call and tool step, the resolved inputs (not the templated ones), the raw outputs. That trace is exactly the unforgeable, agent-didn't-author substrate that Tier 1+2 need to score against. Without it,... - Source: dev.to / 11 days ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
TensorFlow Lite - Low-latency inference of on-device ML models
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Monitor ML - Real-time production monitoring of ML models, made simple.
VS Code - Build and debug modern web and cloud applications, by Microsoft
Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.