Peter Norvig
Director of Research, Google Inc
Book Recommendations:
Recommended by Peter Norvig
“This book is a worthy contribution to the field of text mining. By focusing on classification (rather than exhaustively covering extraction, summarization, and other tasks), it achieves the right balance of coherence and comprehensiveness. It collects papers by the leading authors in the field, who employ and explain a variety of techniques―kernel methods, link analysis, latent Dirichlet allocation, non-negative matrix factorization, and others. Together the papers bring unity and clarity to a disjointed and sometimes perplexing field and serve as the perfect introduction for an advanced student.” (from Amazon)
by Ashok N. Srivastava, Mehran Sahami·You?
by Ashok N. Srivastava, Mehran Sahami·You?
The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the Field Giving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify text documents and applies these methods in a variety of areas, including adaptive information filtering, information distillation, and text search. The book begins with chapters on the classification of documents into predefined categories. It presents state-of-the-art algorithms and their use in practice. The next chapters describe novel methods for clustering documents into groups that are not predefined. These methods seek to automatically determine topical structures that may exist in a document corpus. The book concludes by discussing various text mining applications that have significant implications for future research and industrial use. There is no doubt that text mining will continue to play a critical role in the development of future information systems and advances in research will be instrumental to their success. This book captures the technical depth and immense practical potential of text mining, guiding readers to a sound appreciation of this burgeoning field.
Recommended by Peter Norvig
“With the investigatory skill of a historian for the earliest work, personal recollections and reflections of early work, and unprecedented access to current researchers; and with the wit of a skilled author and teacher and the insight of a founding father, Nils Nilsson is uniquely qualified to present this lucid, comprehensive, entertaining and balanced history of AI.” (from Amazon)
by Nils J. Nilsson·You?
by Nils J. Nilsson·You?
Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today’s AI engineers. AI is becoming more and more a part of everyone’s life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book’s many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
Recommended by Peter Norvig
“A comprehensive overview that avoids the hype and explains what AI can actually do, written by an expert practitioner of the field.” (from Amazon)
A scientist who has spent a career developing Artificial Intelligence takes a realistic look at the technological challenges and assesses the likely effect of AI on the future.How will Artificial Intelligence (AI) impact our lives? Toby Walsh, one of the leading AI researchers in the world, takes a critical look at the many ways in which "thinking machines" will change our world.Based on a deep understanding of the technology, Walsh describes where Artificial Intelligence is today, and where it will take us.·Will automation take away most of our jobs? ·Is a "technological singularity" near? ·What is the chance that robots will take over? ·How do we best prepare for this future? The author concludes that, if we plan well, AI could be our greatest legacy, the last invention human beings will ever need to make.
Recommended by Peter Norvig
“Deep Learning is for everyone” (from Amazon)
by Jeremy Howard, Sylvain Gugger·You?
by Jeremy Howard, Sylvain Gugger·You?
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala