ODSC - Open Data Science

OCTOBER 11, 2023

Be sure to check out his talk, “ How to Practice Data-Centric AI and Have AI Improve its Own Dataset ,” there! Machine learning models are only as good as the data they are trained on. Even with the most advanced neural network architectures, if the training data is flawed, the model will suffer.

Auto-classification 52

Auto-classification Auto-complete Data Drift Machine Learning 52

DataRobot Blog

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Automation Auto-classification 52

AWS Machine Learning Blog

MARCH 1, 2023

Statistical methods and machine learning (ML) methods are actively developed and adopted to maximize the LTV. Challenges In this section, we discuss challenges around various data sources, data drift caused by internal or external events, and solution reusability. The interval of logs is not uniform.

Automation 92

Automation ETL Data Drift ML 92

The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134