Remove AWS Remove Clustering Remove DataOps
article thumbnail

Authoring custom transformations in Amazon SageMaker Data Wrangler using NLTK and SciPy

AWS Machine Learning Blog

You can integrate a Data Wrangler data preparation flow into your machine learning (ML) workflows to simplify data preprocessing and feature engineering, taking data preparation to production faster without the need to author PySpark code, install Apache Spark, or spin up clusters. Sovik Kumar Nath is an AI/ML solution architect with AWS.

AWS 95
article thumbnail

How HR Tech Company Sense Scaled their ML Operations using Iguazio

Iguazio

Iguazio is an essential component in Sense’s MLOps and DataOps architecture, acting as the ML training and serving component of the pipeline. Cost-effectiveness: Sense was able to find the ideal AWS cost and resource allocation balance. The Solution Sense chose Iguazio as their MLOps solution. Enabling quick iterations over feedback.

ML 52
article thumbnail

How Sense Uses Iguazio as a Key Component of Their ML Stack

Iguazio

Iguazio is an essential component in Sense’s MLOps and DataOps architecture, acting as the ML training and serving component of the pipeline. Cost-effectiveness: Sense was able to find the perfect AWS cost and resource allocation balance. The Solution: Iguazio Sense chose Iguazio as their MLOps platform. Enabling quick experimentation.

ML 52