AWS Machine Learning Blog

APRIL 17, 2023

In other words, companies need to move from a model-centric approach to a data-centric approach.” – Andrew Ng A data-centric AI approach involves building AI systems with quality data involving data preparation and feature engineering. Custom transforms can be written as separate steps within Data Wrangler.

AWS 94

AWS ML ML Python 94

Becoming Human

MAY 11, 2023

It covers everything from data preparation and model training to deployment, monitoring, and maintenance. The MLOps process can be broken down into four main stages: Data Preparation: This involves collecting and cleaning data to ensure it is ready for analysis.

Machine Learning 78

Machine Learning Machine Learning DataOps Cloud Computing 78

AWS Machine Learning Blog

JULY 31, 2023

We explain the metrics and show techniques to deal with data to obtain better model performance. Prerequisites If you would like to implement all or some of the tasks described in this post, you need an AWS account with access to SageMaker Canvas. Let’s try to improve the model performance using a data-centric approach.

ML 90

ML ML Data Preparation Machine Learning 90

IBM Journey to AI blog

AUGUST 12, 2024

MLOps prioritizes end-to-end management of machine learning models, encompassing data preparation, model training, hyperparameter tuning and validation. It uses CI/CD pipelines to automate predictive maintenance and model deployment processes, and focuses on updating and retraining models as new data becomes available.

Big Data 106

Big Data Big Data ML ML 106