MLOps, or DevOps for machine learning, is bringing the best practices of software development to data science. You know the saying, “Give a man a fish, and you’ll feed him for a day… Integrate machine ...

作为人工智能的关键基石，能够从过往数据中发现规律、总结知识，并预测趋势洞察的机器学习，正受到越来越多的重视和越来越广泛的应用。从预测疫情发展走向、协调仓储和物流资源、躲避道路交通拥堵、前瞻流行趋势，到“猜你喜欢”的个性化推荐，机器 ...

这些年，我看到许多企业在AI浪潮中重复着同一个遗憾的故事。 某家制造企业，投入了数百万预算，由顶尖团队开发出一套复杂的销售预测模型。模型在实验室测试阶段堪称完美，部署上线后，初期表现也十分亮眼，准确率一度高达92%。决策层为此兴奋不已 ...

我刚开始接触机器学习领域时，认为将模型部署到云环境是最大的挑战。我当时觉得，我只需要把在 Jupyter Notebook 中训练好的机器学习模型部署到云端，就 万事大吉了。 我错了。 起初，一切都按预期进行，大家都对部署的模型感到满意。然而，几个月后，当我 ...

This article is part of a VB special issue. Read the full series here: The quest for Nirvana: Applying AI at scale. To say that it’s challenging to achieve AI at scale across the enterprise would be ...

Once machine learning models make it to production, they still need updates and monitoring for drift. A team to manage ML operations makes good business sense As hard as it is for data scientists to ...

The MLops market may still be hot when it comes to investors. But for enterprise end users, it may seem like a hot mess. The MLops ecosystem is highly fragmented, with hundreds of vendors competing in ...

Security researchers have identified multiple attack scenarios targeting MLOps platforms like Azure Machine Learning (Azure ML), BigML and Google Cloud Vertex AI, among others. According to a new ...