Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...

Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved remarkable ...

The information bottleneck (IB) principle is a powerful information‐theoretic framework that seeks to compress data representations while preserving the information most pertinent to a given task.

Parth is a technology analyst and writer specializing in the comprehensive review and feature exploration of the Android ecosystem. His work is distinguished by its meticulous focus on flagship ...

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 ...

The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...