Nowadays, every company is performing some Machine Learning tasks for various reasons, such as improve customer experience, improve internal processes, and many more. Maintaining the Machine Learning (ML) life cycle is a major challenge a lot of companies are facing these days.

Sagemaker provides an easy option to train and deploy the ML models. It can also capture the tensors during the training phase. This helps in debugging the training step and can save a lot of training time and money, if the training is not progressing as expected. In cases where the input is in unexpected format, sagemaker provides a way to handle the unexpected inputs. Monitoring the deployed model provides an insight on the models and also helps in improving the model.