Machine learning is an exciting area of research and development. ML tools are important in many industries and science fields. ML research is also very tricky and has several challenges. If not addressed suitably, these challenges can lead the project in the wrong direction.
摘要： Rendezvous Architecture helps you run and choose outputs from a Champion model and many Challenger models running in parallel without many overheads. The original approach works well for smaller data sets, so how can this idea adapt to big data pipelines?