We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

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

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a specific approach to reach the same goal.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Using lab-grown brain tissue, researchers uncovered complex patterns of neural signaling that differ subtly between healthy ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...