A comprehensive introduction to machine learning that uses probabilistic models & inference as a unifying approach 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 & then use the uncovered patterns to predict future data This textbook offers a comprehensive & self-contained introduction to the field of machine learning based on a unified probabilistic approach The coverage combines breadth & depth offering necessary background material on such topics as probability optimization & linear algebra as well as discussion of recent developments in the field including conditional random fields L1 regularization & 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 & worked examples drawn from such application domains as biology text processing computer vision & 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 & 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 & beginning graduate students ...

A comprehensive introduction to machine learning that uses probabilistic models & inference as a unifying approach 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 & then use the uncovered patterns to predict future data This textbook offers a comprehensive & self-contained introduction to the field of machine learning based on a unified probabilistic approach The coverage combines breadth & depth offering necessary background material on such topics as probability optimization & linear algebra as well as discussion of recent developments in the field including conditional random fields L1 regularization & 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 & worked examples drawn from such application domains as biology text processing computer vision & 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 & 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 & beginning graduate students ...

As one of the most comprehensive machine learning texts around this book does justice to the field's incredible richness but without losing sight of the unifying principles Peter Flach's clear example-based approach begins by discussing how a spam filter works which gives an immediate introduction to machine learning in action with a minimum of technical fuss Flach provides case studies of increasing complexity & variety with well-chosen examples & illustrations throughout He covers a wide range of logical geometric & statistical models & state-of-the-art topics such as matrix factorisation & ROC analysis Particular attention is paid to the central role played by features The use of established terminology is balanced with the introduction of new & useful concepts & summaries of relevant background material are provided with pointers for revision if necessary These features ensure Machine Learning will set a new standard as an introductory textbook ...

Now that storage & collection technologies are cheaper & more precise methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data With this book you'll learn machine learning & statistics tools in a practical fashion using black-box solutions & case studies instead of a traditional math-heavy presentation By exploring each problem in this book in depth
- including both viable & hopeless approaches
- you'll learn to recognize when your situation closely matches traditional problems Then you'll discover how to apply classical statistics tools to your problem Machine Learning for Hackers is ideal for programmers from private public & academic sectors

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A Proven Hands-On Approach for Students without a Strong Statistical Foundation Since the best-selling first edition was published there have been several prominent developments in the field of machine learning including the increasing work on the statistical interpretations of machine learning algorithms Unfortunately computer science students without a strong statistical background often find it hard to get started in this area Remedying this deficiency Machine Learning An Algorithmic Perspective Second Edition helps students understand the algorithms of machine learning It puts them on a path toward mastering the relevant mathematics & statistics as well as the necessary programming & experimentation New to the Second Edition Two new chapters on deep belief networks & Gaussian processes Reorganization of the chapters to make a more natural flow of content Revision of the support vector machine material including a simple implementation for experiments New material on random forests the perceptron convergence theorem accuracy methods & conjugate gradient optimization for the multi-layer perceptron Additional discussions of the Kalman & particle filters Improved code including better use of naming conventions in Python Suitable for both an introductory one-semester course & more advanced courses the text strongly encourages students to practice with the code Each chapter

Includes:: detailed examples along with further reading & problems All of the code used to create the examples is available on the author's website

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Tracklist A1 Lapis A2 Morphogene A3 Angel Speak A4 Tell U B1 Surfed Out B2 Do It 4 U B3 Celestial Levels B4 Isometrix C1 Colour Communicator C2 Spectrum Sequence C3 White Crown C4 Ocean Of Thought D1 Etheric Body Temple D2 Dos Puertas D3 Opalescent Release date (30 Sept 2016) Number of Discs 2 Label Ninja Tune Genre Electronic Hip Hop Pop Style Juke Trap House Jungle Experimental ...

Tracklist A1 Trouringh 718 A2 Stofstuktoon 637 A3 Ranonkel 1 515 A4 Ranonkel 2 141 B1 Andermansthuis 436 B2 Zink 1709 ...

Explore the military vehicles artillery & industrial weaponry that changed the course of history From the first repeating rifles to the most advanced military technology of the 21st century Machines of War presents a one-of-a-kind illustrated history of modern warfare told through the weapons & vehicles that have dominated the battlefield since the Industrial Revolution Discover vehicles from the Industrial era World War I World War II the Cold War & the modern world Look up-close at the Gatling gun the Spitfire fighter plane the T-72 Tank & many more with virtual tours putting you at the helm of war's most formidable weapons Featuring stunning photographs of key firearms aircraft tanks warships & more Machines Of War offers a uniquely detailed look at the machines that have shaped the modern military world ...

Machines That Think explores how artificial intelligence helps us understand human intelligence machines that compose music & write stories
- & asks if AI is really a threat 288 pages New Scientist
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Have you ever wondered where comedians come from? Why is it that one person is a funny bloke down the pub while another actually makes a living by standing up in front of an audience telling jokes? & where does all that material come from? Well young Lee Mc Killop used to wonder that too Growing up in his parents’ pub small & wiry in a world of bigger & chunkier specimens Lee quickly learned that cracking jokes was a way to get attention After a somewhat random series of jobs which included being Red Rum’s stableboy & a bingo hall barman it was as a Great Yarmouth holiday camp entertainer that he had his first crack at telling jokes on stage It got him some laughs the sack & a punch in the face ...