Sukender Reddy Mallreddy, a Salesforce Consultant and data science expert, explains these concepts in his new book, "Real-Time Data Structures: Innovations for Machine Learning with Streaming Data." ...

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

A crucial part of the machine learning lifecycle is managing data drift to ensure the model remains effective and continues to provide business value. Data is an ever-changing landscape, after all.

The potential for machine learning to transform data-intensive businesses is undeniable, but realizing this potential requires more than just an investment in technology.

The data lakehouse architecture is leading this change—particularly for machine learning (ML) and advanced analytics—by combining the strengths of both data lakes and data warehouses. The ...

Data science platform Kaggle is hosting a Wikipedia dataset that’s specifically optimized for machine learning applications by Jess Weatherbed Apr 17, 2025, 10:07 AM UTC ...