The book Practical Deep Learning may be of interest to Gadget Masters getting serious with use of AI and develop their own ...

Explore 20 essential activation functions implemented in Python for deep neural networks—including ELU, ReLU, Leaky ReLU, ...

Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning!

By the end of the book, you’ll pack everything into a complete Python deep learning library, creating your own class hierarchy of layers, activation functions, and neural network architectures ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions ...

Open source deep learning neural networks are coming of age ... TensorFlow programming interfaces includes Python & C++. With the version 1.0 announcement, alpha releases of Java, GO, R, and ...

It is written in Python and supports multiple back-end neural network computation engines ... why it’s an improvement over low-level deep learning APIs. Keras was created to be user friendly ...

Neural Networks and Deep Learning are the two hot buzzwords used nowadays with Artificial Intelligence. The recent developments in the world of Artificial intelligence can be attributed to these ...

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

speed-of-light artificial neural network. Coined by Rina Dechter in 1986, Deep Learning is one of the fastest-growing methodologies in the machine learning community and is often used in face ...