Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.
The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.
The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
In celebration of Caribbean American Heritage Month in June, we are sharing a collection of books by Caribbean American and Caribbean authors that includes fiction, memoir, non-fiction, and history. Find a full collection of titles here.
On Monday, May 5, three Penguin Random House authors were honored with a Pulitzer Prize. Established in 1917, the Pulitzer Prizes are the most prestigious awards in American letters. To date, PRH has 143 Pulitzer Prize winners, including William Faulkner, Eudora Welty, Josh Steinbeck, Ron Chernow, Anne Applebaum, Colson Whitehead, and many more. Take a look at our 2025 Pulitzer Prize
In June, we celebrate Black Music Appreciation month and the influential Black musicians and artists who have brought entertainment to their communities and beyond, and inspired others to make their own art. Collection of titles for Black Music Appreciation Month
In June we celebrate Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual + (LGBTQIA+) Pride Month, which honors the 1969 Stonewall riots in Manhattan. Pride Month is a time to both celebrate the accomplishments of those in the LGBTQ+ community and recognize the ongoing struggles faced by many across the world who wish to live
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