However, instead of phenotypes, there is increasing interest in using genomic data for gene resource management. We used whole-genome resequencing and common-garden experiments to understand the ...

Moreover, the scalability of Gaussian process regression is still challenging, which suffers from cubic complexity to data size. To improve the scalability while retaining desirable health prediction ...

Python in Excel a Smarter Way to Use External Data Watch this video on YouTube. Stay informed about the latest in Python in Excel by exploring our other resources and articles.

Agricultural remote sensing community is increasingly focusing on enhancing crop mapping accuracy by improving data-driven machine-learning model structures, yet ignoring impact of sampling–model ...

Writing complex data structures in Go can help developers better understand the principles of pointers and references.

Crystal structure prediction (CSP) is an important field of material design. Herein, we propose a novel generative adversarial network model, guided by a data-driven approach and incorporating the ...

The underlying mechanisms of many of Python's built-in data structures and constructs are covered. A number of ADTs and applications are discussed as threads throughout the book to allow for multiple ...

These 183,000 Books Are Fueling the Biggest Fight in Publishing and Tech Use our new search tool to see which authors have been used to train the machines.