Remove Clean Data Remove Events Remove K-nearest Neighbors
article thumbnail

Debugging data to build better and more fair ML applications

Snorkel AI

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. You’ll have different shapes of these pipelines.

ML 52
article thumbnail

Debugging data to build better and more fair ML applications

Snorkel AI

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. You’ll have different shapes of these pipelines.

ML 52
professionals

Sign Up for our Newsletter

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

article thumbnail

Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Analysis: This step involves applying statistical and Machine Learning techniques to analyse the cleaned data and uncover patterns, trends, and relationships.

article thumbnail

[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

The following figure represents the life cycle of data science. It starts with gathering the business requirements and relevant data. Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Why is data cleaning crucial?