BookPearson2020-04-28
By Stuart Russell, Peter Norvig
The standard university textbook covering AI as a field - search, knowledge representation, planning, probabilistic reasoning, machine learning, natural language and robotics - used in more than 1,500 universities.
Why it matters
Most of what a reader encounters elsewhere in this library assumes the vocabulary this book teaches from scratch: it is the reference for anyone who wants the field's foundations in one place before specialising into any one subfield.
Key takeaways
Part of these reading paths
Related
Academic resourceGaoling School of Artificial Intelligence, Renmin University of China (with Université de Montréal)2023-03-31
A continuously updated academic survey covering the background, key findings and mainstream techniques of large language models, organised around pre-training, adaptation tuning, utilisation and capability evaluation.
Research paperGoogle Brain / Google Research2017-06-12
The paper that introduced the Transformer architecture - a sequence model built entirely on attention mechanisms, with no recurrence or convolution - and became the architectural basis for essentially every large language model that followed it.
DatasetStanford University / Princeton University2009-06
The image dataset and accompanying paper that, organised on WordNet's noun hierarchy, became the standard benchmark for image classification research through the annual ImageNet Large Scale Visual Recognition Challenge (ILSVRC).
