Unboxing the Magical Machine Learning Blackbox using Sagemaker
September 8, 2020
from 4:00 PM
to 5:00 PM CEST
Train and deploy Machine Learning Models using Sagemaker
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.
Join this Data Reply Webinar and get insights how to use Sagemaker in Machine Learning to train and deploy the model:
Learn how to train models using Sagemaker.
Get to know different debugging options with the ML models during training time.
Get to know various options of deploying the model using Sagemaker.
Monitor the deployed model and identify violations in the input.
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