Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

The deep learning pioneers believe that better neural network architectures will eventually lead to all aspects of human and animal intelligence, including symbol manipulation, reasoning, causal ...

Deep Learning: It is a kind of machine learning which has a human brain-like structure. It works on the basis of logical assembly of algorithms which are known as neural networks.

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch.

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Deep learning is a friendly facet of machine learning that lets AI sort through data and information in a manner that emulates the human brain’s neural network.

Deep learning's capabilities differ in several key respects from traditional shallow machine learning, allowing computers to solve many complex problems. This technology uses neural networks, a ...

Artificial Neural Networks: Learning by Doing Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.