2023年3月7日
Open-source technologies have had a profound impact on the world of AI and machine learning, enabling developers, data scientists, and organizations to collaborate, innovate, and build better AI solutions. At Azure Open Source Day, we highlighted Microsoft’s commitment to open source and how to build intelligent apps faster and with more flexibility using the latest open-source technologies that are available in Azure AI.
2022年7月12日
The growing adoption of data-driven and machine learning-based solutions is driving the need for businesses to handle growing workloads, exposing them to extra levels of complexities and vulnerabilities. Here are some key approaches and tests for securing your machine learning systems against attacks with Azure Machine Learning using MLOps.
2022年6月30日
The capacity of a system to adjust to changes by adding or removing resources to meet demand is known as scalability. Here are some tests to check the scalability of your MLOps model.
2022年6月22日
Robustness is the ability of a closed-loop system to tolerate perturbations or anomalies while system parameters are varied over a wide range. There are three essential tests to ensure that the machine learning system is robust in the production environments: unit tests, data and model testing, and integration testing.
2022年6月14日
機械学習システム開発のライフ サイクルにおいて、テストは高品質な運用を保証するための重要な作業です。このブログでは、機械学習システムのテストを機械学習運用 (MLOps) の観点から見て、堅牢でスケーラブル、かつ安全な機械学習システムを構築するために使用できる優れた事例の実践とテスト フレームワークについて学んでいきます。