The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

In today’s fast-changing data landscape, having a strong data system and advanced analytical tools is key to getting valuable insights and staying ahead of the competition. The data lakehouse ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...

Overview: Python and SQL form the core data science foundation, enabling fast analysis, smooth cloud integration, and ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional materials. Materials scientists are therefore working to develop and improve new ...