When we look very closely at images generated by neural networks, we often see a strange checkerboard pattern of artifacts. It’s more obvious in some cases than others, but a large fraction of recent models exhibit this behavior. Mysteriously, the checkerboard pattern tends to be most prominent in images with strong colors. What’s going on? Read more about Deconvolution and Checkerboard Artifacts — Distill[…]

A popular method for exploring high-dimensional data is something called t-SNE, introduced by van der Maaten and Hinton in 2008. The technique has become widespread in the field of machine learning, since it has an almost magical ability to create compelling two-dimensonal “maps” from data with hundreds or even thousands of dimensions. Although impressive, these Read more about How to Use t-SNE Effectively — Distill[…]

Recurrent neural networks are one of the staples of deep learning, allowing neural networks to work with sequences of data like text, audio and video. They can be used to boil a sequence down into a high-level understanding, to annotate sequences, and even to generate new sequences from scratch! Source: Attention and Augmented Recurrent Neural Read more about Attention and Augmented Recurrent Neural Networks — Distill[…]

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. Source: Deep Learning

Neural Networks and Deep Learning is a free online book. The book will teach you about: Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data Deep learning, a powerful set of techniques for learning in neural networks Neural networks and deep learning currently provide the best solutions to Read more about Neural networks and deep learning[…]