ODSC - Open Data Science

MAY 10, 2023

Although tabular data are less commonly required to be labeled, his other points apply, as tabular data, more often than not, contains errors, is messy, and is restricted by volume. One might say that tabular data modeling is the original data-centric AI!

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

ODSC - Open Data Science

APRIL 13, 2023

Hands-on Data-Centric AI: Data Preparation Tuning — Why and How? Going into developing machine learning models with a hands-on, data-centric AI approach has its benefits and requires a few extra steps to achieve.

ML 52

ML ML Data Science Machine Learning 52

phData

MARCH 13, 2024

Alteryx is a data analytics platform that stands out for its ability to simplify complex data processes. It integrates data preparation, blending, and analysis, making it a go-to solution for analysts and data professionals.

Analytics 52

Analytics Analytics Data Preparation 52

phData

AUGUST 8, 2023

RAPIDS offers a familiar Python interface akin to popular data science tools like Pandas and Scikit-Learn but with GPU-accelerated capabilities. This provides dramatic speed improvements in data preparation and machine learning tasks and the ability for more iterative data exploration and model development.

AI 52

AI AI Deep Learning Deep Learning 52

Pickl AI

NOVEMBER 28, 2024

Data Transformation Transforming data prepares it for Machine Learning models. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding. Outlier detection identifies extreme values that may skew results and can be removed or adjusted.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Step 5: Networking and Seeking Opportunities in the Field Networking is crucial for career development, especially in the Data Science community.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Precisely

SEPTEMBER 26, 2024

Above all, you must remember that trusted AI starts with trusted data. And trusted data requires data integrity: data that’s accurate, consistent, and contextualized. Without proper data preparation, you risk issues like bias and hallucination, inaccurate predictions, poor model performance, and more. “If

AI 75

AI AI Data Governance Data Quality 75

Iguazio

MARCH 20, 2025

To see the complete conversation and dive into their insights, watch the webinar here. See the webinar for more Gartner trends. The Enterprise AI Factory The enterprise AI factory includes: Data management - Curating data, preparing it, ingestion, etc. Watch the webinar to see. Whats Next in 2025?

AI 59

AI AI Data Pipeline Data Scientist 59

Data Science Dojo

APRIL 3, 2025

A well-structured data pipeline ensures that AI applications work with clean, reliable, and regulatory-compliant data. The Databricks + Gencore AI integration simplifies this by automating data preparation, cleaning, and governance.

AI 195

AI AI Data Pipeline Data Preparation 195