Remove 2021 Remove Data Preparation Remove Machine Learning
article thumbnail

Alternative Feature Selection Methods in Machine Learning

KDnuggets

Feature selection methodologies go beyond filter, wrapper and embedded methods. In this article, I describe 3 alternative algorithms to select predictive features based on a feature importance score.

article thumbnail

Achieve effective business outcomes with no-code machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

On November 30, 2021, we announced the general availability of Amazon SageMaker Canvas , a visual point-and-click interface that enables business analysts to generate highly accurate machine learning (ML) predictions without having to write a single line of code.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Hands-on Data-Centric AI: Data Preparation Tuning?—?Why and How?

ODSC - Open Data Science

Hands-on Data-Centric AI: Data Preparation Tuning — Why and How? Be sure to check out her talk, “ Hands-on Data-Centric AI: Data preparation tuning — why and how? Machine Learning is applied to an increasingly large number of applications that range from financial to healthcare industries.

article thumbnail

Building an efficient MLOps platform with OSS tools on Amazon ECS with AWS Fargate

AWS Machine Learning Blog

As an early adopter of large language model (LLM) technology, Zeta released Email Subject Line Generation in 2021. Zeta’s AI innovation is powered by a proprietary machine learning operations (MLOps) system, developed in-house. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

AWS 128
article thumbnail

What is MLOps

Towards AI

Pietro Jeng on Unsplash MLOps is a set of methods and techniques to deploy and maintain machine learning (ML) models in production reliably and efficiently. Thus, MLOps is the intersection of Machine Learning, DevOps, and Data Engineering (Figure 1). Projects: a standard format for packaging reusable ML code.

article thumbnail

How are AI Projects Different

Towards AI

The MLOps Process We can see some of the differences with MLOps which is a set of methods and techniques to deploy and maintain machine learning (ML) models in production reliably and efficiently. MLOps is the intersection of Machine Learning, DevOps, and Data Engineering. References [1] E. Russell and P.

article thumbnail

AWS positioned in the Leaders category in the 2022 IDC MarketScape for APEJ AI Life-Cycle Software Tools and Platforms Vendor Assessment

AWS Machine Learning Blog

The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning (ML) model development, including data preparation, model building and training, model operation, evaluation, deployment, and monitoring. About the author.

AWS 95