#networks
Explore Books, Authors and Common Highlights on Networks
Showing 13 of 13 highlights
Convolutional neural networks (CNNs) have proven to be very effective for image processing tasks.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
In systems, everything is connected to everything else.
Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Deep learning is a subfield of machine learning that uses algorithms inspired by the structure and function of the brain.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
The connections between people are as vital as the connections between places.
From The Ghost Map by Steven Johnson
Life is a web of interactions.
From Entangled Life by Merlin Sheldrake
Training deep networks is challenging due to issues like vanishing gradients and requires careful initialization.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
The choice of activation function can greatly influence the performance of a neural network.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Training a deep network involves adjusting the weights of connections based on the error of the output.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Networks, like cities, thrive on the diversity of their components.
From Scale by Geoffrey West
The world is a series of nested networks.
From Entangled Life by Merlin Sheldrake
Mycelium is both a network and a community.
From Entangled Life by Merlin Sheldrake
Understanding the nature of networks can help us solve many of the challenges we face today.
From Scale: The Universal Laws of Life and Death in Organisms, Cities and Companies by Geoffrey West