Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

Overview: NumPy is ideal for data analysis, scientific computing, and basic ML tasks.PyTorch excels in deep learning, GPU ...

A new study introduces a universal two-stage method that successfully segments plant stems and leaves across both monocotyledonous and dicotyledonous crops.

Abstract: Training deep learning models is computationally demanding and data-intensive. Existing approaches utilize local SSDs within training servers to cache datasets, thereby accelerating data ...

Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks you through loading the MNIST dataset, creating a neural network, training ...

President Donald Trump is expected to approve a proposed deal this week that would ensure TikTok in the United States is majority-owned by American investors and keep user data in a "trusted" cloud in ...

Jessie Mahr led a team that restored critical climate data removed from public access under the Trump administration. Now, she’s pioneering a wider effort to fill data gaps in federal policy. Former ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

SCDL seems to me to have two parts: a format for efficient access to row-wise data, and a PyTorch Dataset derivative. The former has many uses beyond PyTorch and the project I work on explicitly tries ...