A First Course In Machine Learning
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A First Course In Machine Learning
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Author : Simon Rogers
language : en
Publisher: CRC Press
Release Date : 2016-10-14
A First Course In Machine Learning written by Simon Rogers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-14 with Business & Economics categories.
"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC." —Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden "This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade." —Daniel Barbara, George Mason University, Fairfax, Virginia, USA "The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing ‘just in time’ the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts." —Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark "I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength...Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months." —David Clifton, University of Oxford, UK "The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book." —Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK "This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning...The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective." —Guangzhi Qu, Oakland University, Rochester, Michigan, USA
A First Course In Machine Learning Solutions Manual
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Author : Taylor & Francis Group
language : en
Publisher:
Release Date : 2011-10-24
A First Course In Machine Learning Solutions Manual written by Taylor & Francis Group and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-24 with categories.
A First Course In Machine Learning
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Author : Mark Girolami
language : en
Publisher: CRC Press
Release Date : 2015-09-15
A First Course In Machine Learning written by Mark Girolami and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Business & Economics categories.
A First Course in Machine Learning covers the core mathematical and statistical techniques needed to understand some of the most popular machine learning algorithms. The algorithms presented span the main problem areas within machine learning: classification, clustering and projection. The text gives detailed descriptions and derivations for a small number of algorithms rather than cover many algorithms in less detail. Referenced throughout the text and available on a supporting website (http://bit.ly/firstcourseml), an extensive collection of MATLAB®/Octave scripts enables students to recreate plots that appear in the book and investigate changing model specifications and parameter values. By experimenting with the various algorithms and concepts, students see how an abstract set of equations can be used to solve real problems. Requiring minimal mathematical prerequisites, the classroom-tested material in this text offers a concise, accessible introduction to machine learning. It provides students with the knowledge and confidence to explore the machine learning literature and research specific methods in more detail.
A First Course In Artificial Intelligence
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Author : Osondu Oguike
language : en
Publisher: Bentham Science Publishers
Release Date : 2021-07-13
A First Course In Artificial Intelligence written by Osondu Oguike and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-13 with categories.
The importance of Artificial Intelligence cannot be over-emphasised in current times, where automation is already an integral part of industrial and business processes. A First Course in Artificial Intelligence is a comprehensive textbook for beginners which covers all the fundamentals of Artificial Intelligence. Seven chapters (divided into thirty-three units) introduce the student to key concepts of the discipline in simple language, including expert system, natural language processing, machine learning, machine learning applications, sensory perceptions (computer vision, tactile perception) and robotics. Each chapter provides information in separate units about relevant history, applications, algorithm and programming with relevant case studies and examples. The simplified approach to the subject enables beginners in computer science who have a basic knowledge of Java programming to easily understand the contents. The text also introduces Python programming language basics, with demonstrations of natural language processing. It also introduces readers to the Waikato Environment for Knowledge Analysis (WEKA), as a tool for machine learning. The book is suitable for students and teachers involved in introductory courses in undergraduate and diploma level courses which have appropriate modules on artificial intelligence.
A First Course In Monte Carlo
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Author : George S. Fishman
language : en
Publisher: Duxbury Resource Center
Release Date : 2006
A First Course In Monte Carlo written by George S. Fishman and has been published by Duxbury Resource Center this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
A FIRST COURSE IN MONTE CARLO shows you how to design, perform, and analyze the results of MC experiments based on independent replications, Markov chain MC, and MC optimization. The text emphasizes the variance-reducing techniques of importance sampling, stratified sampling, Rao-Blackwellization, control variates, antithetic variates, and quasi-random numbers. For solving optimization problems it describes several MC techniques, including simulated annealing, simulated tempering, swapping, stochastic tunneling, and genetic algorithms. Examples from many areas show how these techniques perform in practice. Hands-on exercises allow you to experience challenges encountered when solving real problems. An answer key to selected problems is included.
A First Course In Physics
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Author : Herbert Brownell
language : en
Publisher:
Release Date : 1929
A First Course In Physics written by Herbert Brownell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1929 with Physics categories.
A First Course In Statistical Learning
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Author : Johannes Lederer
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
A First Course In Statistical Learning written by Johannes Lederer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Computers categories.
This textbook introduces the fundamental concepts and methods of statistical learning. It uses Python and provides a unique approach by blending theory, data examples, software code, and exercises from beginning to end for a profound yet practical introduction to statistical learning. The book consists of three parts: The first one presents data in the framework of probability theory, exploratory data analysis, and unsupervised learning. The second part on inferential data analysis covers linear and logistic regression and regularization. The last part studies machine learning with a focus on support-vector machines and deep learning. Each chapter is based on a dataset, which can be downloaded from the book's homepage. In addition, the book has the following features: A careful selection of topics ensures rapid progress. An opening question at the beginning of each chapter leads the reader through the topic. Expositions are rigorous yet based on elementary mathematics. More than two hundred exercises help digest the material. A crisp discussion section at the end of each chapter summarizes the key concepts and highlights practical implications. Numerous suggestions for further reading guide the reader in finding additional information. This book is for everyone who wants to understand and apply concepts and methods of statistical learning. Typical readers are graduate and advanced undergraduate students in data-intensive fields such as computer science, biology, psychology, business, and engineering, and graduates preparing for their job interviews.
Machine Learning
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Author : Andreas Lindholm
language : en
Publisher:
Release Date : 2022
Machine Learning written by Andreas Lindholm and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Machine learning categories.
"This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning"--
A First Course In English Literature
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Author : Richard Wilson
language : en
Publisher:
Release Date : 1903
A First Course In English Literature written by Richard Wilson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1903 with English literature categories.
First Course In General Science
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Author : Frederic Delos Barber
language : en
Publisher:
Release Date : 1916
First Course In General Science written by Frederic Delos Barber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1916 with Science categories.