Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

A new technical paper titled “Deep-learning atomistic semi-empirical pseudopotential model for nanomaterials” was published ...

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee (Seoul National ...

Machine learning and deep learning are both parts of artificial intelligence, but they work in different ways — like a smart student versus a super-specialised ...

Speaking of Alphabet, it would definitely be possible for both Microsoft and Alphabet to appreciate 50% in 2026. While ...

A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...