Data Preparation, Data Science and DataOps

AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

AUGUST 12, 2024

Here, we’ll discuss the key differences between AIOps and MLOps and how they each help teams and businesses address different IT and data science challenges. MLOps prioritizes end-to-end management of machine learning models, encompassing data preparation, model training, hyperparameter tuning and validation.

Big Data

Big Data Big Data ML ML

Is your model good? A deep dive into Amazon SageMaker Canvas advanced metrics

AWS Machine Learning Blog

JULY 31, 2023

Data preparation, feature engineering, and feature impact analysis are techniques that are essential to model building. These activities play a crucial role in extracting meaningful insights from raw data and improving model performance, leading to more robust and insightful results.

ML ML Data Preparation Machine Learning

Data Science Current

AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

Is your model good? A deep dive into Amazon SageMaker Canvas advanced metrics

Webinars

Stay Connected