Скачать с ютуб Training custom models on Vertex AI в хорошем качестве

Training custom models on Vertex AI

A managed ML training service can help you automate experimentation at scale or retain models for a production application. In this episode of Prototype to Production, Developer Advocate, Nikita Namjoshi, walks through the steps required to train custom models on Vertex AI. Watch along and learn about the benefits of a managed training service that helps keep your results fresh. Chapters: 0:00 - Intro 0:22 - Why do I need a machine learning training service? 1:26 - What are containers? 2:19 - Update custom training code 3:23 - Cloud storage for machine learning 4:50 - Containerizing code for machine learning 5:39 - Dockerfile syntax 6:42 - How to store container images in Google Cloud 7:21 - How to launch a training job on Vertex AI 8:12 - Wrap up Training a custom model on Vertex AI codelab → https://goo.gle/3w7kGvV GCS Fuse on Vertex AI Training → https://goo.gle/3QtwxN0 Writing Dockerfiles for Vertex AI Training → https://goo.gle/3po8mDO Vertex AI Training pre built containers → https://goo.gle/3JXYdXO Vertex AI Training docs → https://goo.gle/3do3eN6 Prototype To Production playlist → https://goo.gle/PrototypeToProduction Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech ​​ #Prototype2Production