Towards AI

FEBRUARY 11, 2025

This method not only expands the available training data but also enhances model efficiency and problem-solving abilities. Ive been a Data Engineering guy for the last decade, so my solution for bad data is immediately a technical solution like below more cleaning scripts, better validation rules, improved monitoring dashboards.

Data Quality 54

Data Quality Data Engineering Data Engineering Data Engineering 54

Dataconomy

JULY 28, 2023

Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data. The choice of approach depends on the impact of missing data on the overall dataset and the specific analysis or model being used.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

phData

FEBRUARY 7, 2024

Snowpark Use Cases Data Science Streamlining data preparation and pre-processing: Snowpark’s Python, Java, and Scala libraries allow data scientists to use familiar tools for wrangling and cleaning data directly within Snowflake, eliminating the need for separate ETL pipelines and reducing context switching.

Python 52

Python ML ML SQL 52

DagsHub

OCTOBER 23, 2024

Now that you know why it is important to manage unstructured data correctly and what problems it can cause, let's examine a typical project workflow for managing unstructured data. DagsHub's Data Engine DagsHub's Data Engine is a centralized platform for teams to manage and use their datasets effectively.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52