Home AI Weirdness Book: You look like a thing About Janelle Subscribe Search Sign in Sign up AI Weirdness: the strange side of machine learning Pokemon generated by neural network By Janelle Shane On July 22, 2016 - 1 min read I’ve been playing around with char-rnn, an open-source torch add-on for character-based neural networks by Andrej Karpathy , using it to generate everything from cookbook recipes to superhero names to a Lovecraft/cookbook mashup . I decided to train the neural network to randomly
Image recognition technology may be sophisticated, but it is also easily duped. Researchers have fooled algorithms into confusing two skiers for a dog, a
Energy-based models for associative memory and generative learning: Hopfield networks, Boltzmann machines, RBMs, and contrastive divergence
My talk at ICSI-the International Computer Science Institute at UC Berkeley. ICSI is a leading independent, nonprofit center for research in computer science. Why Deep Learning Works: Self Regularization in Neural Networks Presented Thursday, December 13, 2018 https://www.youtube.com/watch?v=6Zgul4oygMc The slides are available on my slideshare. The supporting tool, WeightWatcher, can be installed using
Skip to content Publish AI, ML & data-science insights to a global community of data professionals. Sign in Submit an Article Toggle Mobile Navigation Toggle Search Search Data Science Deep Learning Illustrated, Part 2: How Does a Neural Network Learn? An illustrated and intuitive guide to Neural Networks Shreya Rao Feb 8, 2024 14 min read Share Welcome to Part 2 of the Deep Learning Illustrated series. In the previous article (definitely read that first!), we covered how a neural network works and how a tr
GraphRec uses GNNs with opinion-aware interactions and social ties to boost recommendation accuracy, outperforming traditional models on Ciao and Epinions.
An concise overview of a recent paper which introduces a new way to perturb networks during training in order to improve their performance, stochastic depth networks
Practicing a new habit under these four conditions can change millions and possibly billions of brain connections. The discovery of neural plasticity is a breakthrough that has significantly altered our understanding of how to change habits, increase happiness, improve health & change our genes
We have developed a search algorithm based on neural networks. Compared to our previous algorithm, the new algorithm shows relevant products up to 23% more often and up to 14% more accurately predicts the next product a user will interact with. We tell you about the other benefits in the article. Key benefits of the
We demonstrate how to code a Artificial neural network model and train and save it in JSON or H5 format which can be loaded later for any inference task. We use Keras/ TensorFlow to demonstrate this transfer learning and used Pima Indian Diabetes dataset in CSV format