A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

Abstract: Dimensionality reduction methods are employed to decrease data dimensionality, either to enhance machine learning performance or to facilitate data visualization in two or three-dimensional ...

Through AI frameworks and libraries, businesses can build and craft their AI solutions to realise efficiencies and optimisations that yield real returns Software plays a crucial role in streamlining ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Design is an iterative process of creating a structure and telling a story. The structure provides utility, while the story fosters connection. Although the design process is dynamic, I often find ...

Causal inference has been increasingly essential in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional ...

Pandas is a robust data manipulation library that offers high-performance, user-friendly data structures and analytical tools in Python. Pandas enables users to import, clean, transform, and analyze ...

Python stands out as a widely embraced and versatile programming language in the realm of data science. Whether you are a beginner or an expert, many books can help you learn new skills, explore new ...