By analysing videos of penalty kicks, a deep learning model was able to predict whether a shot would go to the goalkeeper’s ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Understand the power of word embeddings in deep learning — with detailed Python and RNN integration. #RNN #WordEmbeddings ...

Key Takeaways X, Facebook, and LinkedIn offer data roles across product, marketing, and AI.These jobs require strong skills ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Scikit-learn, PyTorch, and TensorFlow remain core tools for structured data and deep learning tasks.New libraries like JAX, ...

Time series prediction with neural networks has been the focus of much research in the past few decades. Given the recent deep learning revolution, there has been much attention in using deep learning ...

We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based ...

This study harnesses physiological data collected from wearable sensors to construct a series of data-driven models based on deep learning approaches. We systematically compare these models to offer ...