KDnuggets

JULY 5, 2022

Leverage the powerful data wrangling tools in R’s dplyr to clean and prepare your data.

Data Preparation 400

Data Preparation Data Wrangling Data Science 400

ODSC - Open Data Science

MARCH 13, 2023

Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, data wrangling, and data preparation.

Machine Learning 94

Machine Learning Machine Learning Data Wrangling Data Science 94

Alation

FEBRUARY 20, 2020

On August 25 at 11am PDT, Forrester’s VP and Research Director, Gene Leganza, Alation’s Head of Product, Aaron Kalb, and Trifacta’s Director of Product Marketing, Will Davis, will hold a webinar to discuss “Achieving Productivity with Self-Service Data Preparation.”

Data Analysis 52

Data Analysis Data Analysis Data Wrangling Data Preparation 52

Towards AI

JUNE 27, 2023

To prepare the data for models, a data scientist often needs to transform, clean, and enrich the dataset. Fortunately, SageMaker’s data-wrangling capabilities allow data scientists to quickly and efficiently transform and review the transformed data.

AWS 52

AWS Data Scientist Data Wrangling Data Preparation 52

Pickl AI

APRIL 10, 2023

Data Analysts need deeper knowledge on SQL to understand relational databases like Oracle, Microsoft SQL and MySQL. Moreover, SQL is an important tool for conducting Data Preparation and Data Wrangling.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

ODSC - Open Data Science

JANUARY 29, 2024

Databricks: Powered by Apache Spark, Databricks is a unified data processing and analytics platform, facilitates data preparation, can be used for integration with LLMs, and performance optimization for complex prompt engineering tasks. Kubernetes: A long-established tool for containerized apps.

Machine Learning 52

Machine Learning Machine Learning Data Science Natural Language Processing 52

Snorkel AI

APRIL 13, 2023

We can’t send private data such as medical records to an API, and therefore we need small open-source models to improve the feasibility of our proposal. A next huge challenge is data preparation, or data wrangling tasks, such as identifying and filling in missing values or detecting data entry errors and databases.

Data Wrangling 52

Data Wrangling Machine Learning Machine Learning ML 52