This book explores inductive inference using the minimum message length (MML) principle, a Bayesian method which is a realisation of Ockham's Razor based on information theory. Accompanied by a library of software, the book can assist an applications programmer, student or researcher in the fields of data analysis and machine learning to write computer programs based upon this principle.MML inference has been around for 50 years and yet only one highly technical book has been writt...

For fans of Jack Reacher, Tanya Scott’s debut thriller introduces listeners to Luke Harris, a man trying to move beyond his criminal past but finds himself forced back into his old life and a deadly battle to survive.When Jack Quinlan’s mother dies of a drug overdose, it’s not his father that raises him, but Gus—a ruthless crime boss who sees Jack for what he is: a whip-smart kid with untapped potential. It doesn’t take long for Gus to forge Jack into a weapon....

For ten years, Logan Booth served as a contract killer for the CIA – he just never knew it. The first book in a blockbuster thriller series from Matt Rogers, million-copy bestseller and 'a bright new talent shaking up the genre ' (Candice Fox).In the twilight of his career, Logan learns he has been a vessel for furthering government interests, not a rogue hitman for a band of vigilantes. The revelation destroys him.But when Jorge Romero – a...

They Messed with the Wrong WomenBest mates Teddy and Alice are hired hands with flexible moral boundaries. Whatever the mess, they can be relied upon to fix it with no questions asked. But sometimes it's not as simple as cleaning up.Teddy is searching the suburbs for a missing teenager with her occasional sidekick Art, while Alice's mission is to drive one of Australia's richest men along Victoria's east coast to his final resting place before anybody finds out he's dead. B...

'A sure-fire page-turner that keeps readers guessing' DAILY TELEGRAPH'Shelley Burr does not take prisoners. Crime fiction at its effortless best - beautifully drawn characters, rich relationships, fast and fascinating plot, and twists that make you go "ah"' LAINIE ANDERSON'VANISH delivers a surprising climax worthy of Shelley's reputation as one of Australia's most exciting new crime writers' THE AUSTR...

A DANGEROUS CHASE. A SADISTIC KILLER.DS Lucas Walker is on assignment for the AFP, and it couldn't be more personal. This is his last chance to take down Stefan Markovich - the Vandals leader who tried to have him killed after Walker uncovered his drug operation, and has evaded justice for years.Having tracked Markovich to Berlin, Walker heads to Germany to lure his nemesis out of hiding and into custody. And there is another draw for Walke...

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning.You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and...

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guideKey Features\[\*\] Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide.\[\*\] Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation.\[\*\] Get a solid foundation for your entr...

We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.The updated second edition of this book describes the intuition behind these innovations without jargon or comple...

This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The authors’ reformulation of the identification problem in the light of regularization theory not only...

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applications

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and l...