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Zbirka: Strojno učenje
150 rezultatov
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Machine Learning - A First Course for Engineers and Scientists(2022) ANDREAS LINDHOLMVezava: Trda93,27 €
ANDREAS LINDHOLM
Machine Learning - A First Course for Engineers and Scientists
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Machine Learning for Computer Scientists and Data Analysts(2022) RAFATIRAD, SETAREH,HOMAYOUN, HOUMAN,CHEN, ZHIQIAN,PUDUKOTAI DINAKARRAO, SAI MANOJThis textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks.141,74 €
RAFATIRAD, SETAREH,HOMAYOUN, HOUMAN,CHEN, ZHIQIAN,PUDUKOTAI DINAKARRAO, SAI MANOJ
Machine Learning for Computer Scientists and Data Analysts
This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks.
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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy(2017) CATHY O’NEIL , CATHY O`NEILVezava: Mehka15,27 €
CATHY O’NEILCATHY O`NEIL
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
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Machine Learning for Engineers - Using data to solve problems for physical systems(2021) MCCLARREN, RYAN G.All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging.106,85 €
MCCLARREN, RYAN G.
Machine Learning for Engineers - Using data to solve problems for physical systems
All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging.
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High-Dimensional Data Analysis with Low-Dimensional Models(2022) WRIGHT, JOHN (COLUMBIA UNIVERSITY, NEW YORK),MA, YI (UNIVERSITY OF CALIFORNIA, BERKELEY)A systematic introduction to the theory, algorithms, and applications of key mathematical models for data science. Covering applications including imaging, communication, and face recognition, with online code, it is ideal for senior/graduate students in106,84 €
WRIGHT, JOHN (COLUMBIA UNIVERSITY, NEW YORK),MA, YI (UNIVERSITY OF CALIFORNIA, BERKELEY)
High-Dimensional Data Analysis with Low-Dimensional Models
A systematic introduction to the theory, algorithms, and applications of key mathematical models for data science. Covering applications including imaging, communication, and face recognition, with online code, it is ideal for senior/graduate students in
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Compressive Imaging: Structure, Sampling, Learning(2021) ADCOCK, BEN (SIMON FRASER UNIVERSITY, BRITISH COLUMBIA),HANSEN, ANDERS C. (UNIVERSITY OF CAMBRIDGE)This book provides a practical introduction to compressive imaging (with examples and code), an overview of core topics, and a comprehensive, rigorous treatment of the subject. It caters to graduate students, postdocs and faculty in mathematics, computer106,84 €
ADCOCK, BEN (SIMON FRASER UNIVERSITY, BRITISH COLUMBIA),HANSEN, ANDERS C. (UNIVERSITY OF CAMBRIDGE)
Compressive Imaging: Structure, Sampling, Learning
This book provides a practical introduction to compressive imaging (with examples and code), an overview of core topics, and a comprehensive, rigorous treatment of the subject. It caters to graduate students, postdocs and faculty in mathematics, computer
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Bandit Algorithms(2020) LATTIMORE, TOR (UNIVERSITY OF ALBERTA),SZEPESVARI, CSABA (UNIVERSITY OF ALBERTA)Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for g71,22 €
LATTIMORE, TOR (UNIVERSITY OF ALBERTA),SZEPESVARI, CSABA (UNIVERSITY OF ALBERTA)
Bandit Algorithms
Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for g
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Machine Learning Refined(2020) WATT, JEREMY (NORTHWESTERN UNIVERSITY, ILLINOIS),BORHANI, REZA (NORTHWESTERN UNIVERSITY, ILLINOIS),KATSAGGELOS, AGGELOS K. (NORTHWESTERN UNIVERSITY, ILLINOIS)An intuitive approach to machine learning detailing the key concepts needed to build products and conduct research. Featuring color illustrations, real-world examples, practical coding exercises, and an online package including sample code, data sets, lec98,36 €
WATT, JEREMY (NORTHWESTERN UNIVERSITY, ILLINOIS),BORHANI, REZA (NORTHWESTERN UNIVERSITY, ILLINOIS),KATSAGGELOS, AGGELOS K. (NORTHWESTERN UNIVERSITY, ILLINOIS)
Machine Learning Refined
An intuitive approach to machine learning detailing the key concepts needed to build products and conduct research. Featuring color illustrations, real-world examples, practical coding exercises, and an online package including sample code, data sets, lec
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Communicating with Data(2021) ALLCHIN, CARLWith this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.82,08 €
ALLCHIN, CARL
Communicating with Data
With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.
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Deep Learning on Graphs(2021) MA, YAO (MICHIGAN STATE UNIVERSITY),TANG, JILIANG (MICHIGAN STATE UNIVERSITY)This comprehensive text on the theory and techniques of graph neural networks takes students, practitioners, and researchers from the basics to the state of the art. It systematically introduces foundational topics such as filtering pooling, robustness, a79,71 €
MA, YAO (MICHIGAN STATE UNIVERSITY),TANG, JILIANG (MICHIGAN STATE UNIVERSITY)
Deep Learning on Graphs
This comprehensive text on the theory and techniques of graph neural networks takes students, practitioners, and researchers from the basics to the state of the art. It systematically introduces foundational topics such as filtering pooling, robustness, a
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How AI Is Transforming the Organization(2020) REVIEW, MIT SLOAN MANAGEMENT (PAUL MICHELMAN)31,96 €
REVIEW, MIT SLOAN MANAGEMENT (PAUL MICHELMAN)
How AI Is Transforming the Organization
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Probabilistic Numerics - Computation as Machine Learning(2022) HENNIG, PHILIPP (EBERHARD-KARLS-UNIVERSITAT TUBINGEN, GERMANY),OSBORNE, MICHAEL A. (UNIVERSITY OF OXFORD),KERSTING, HANS P. (ECOLE NORMALE SUPERIEURE, PARIS)This text provides a first comprehensive introduction to probabilistic numerics, aimed at Masters' and PhD students, as well as postgraduate researchers in artificial intelligence, computer science, statistics, and applied mathematics. It contains extensi93,27 €
HENNIG, PHILIPP (EBERHARD-KARLS-UNIVERSITAT TUBINGEN, GERMANY),OSBORNE, MICHAEL A. (UNIVERSITY OF OXFORD),KERSTING, HANS P. (ECOLE NORMALE SUPERIEURE, PARIS)
Probabilistic Numerics - Computation as Machine Learning
This text provides a first comprehensive introduction to probabilistic numerics, aimed at Masters' and PhD students, as well as postgraduate researchers in artificial intelligence, computer science, statistics, and applied mathematics. It contains extensi
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Elements of Causal Inference(2017) PETERS, JONAS (ASSOCIATE PROFESSOR OF STATISTICS, UNIVERSITY OF COPENHAGEN),JANZING, DOMINIK (SENIOR RESEARCH SCIENTIST, MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS),SCHOLKOPF, BERNHARD (DIRECTOR OF THE MAX PLANCK INSTITUTE FOR INTELLIGENT IN TUBINGEN, GERMANY, PROFESSOR FOR MACHINE LEA, MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS)61,99 €
PETERS, JONAS (ASSOCIATE PROFESSOR OF STATISTICS, UNIVERSITY OF COPENHAGEN),JANZING, DOMINIK (SENIOR RESEARCH SCIENTIST, MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS),SCHOLKOPF, BERNHARD (DIRECTOR OF THE MAX PLANCK INSTITUTE FOR INTELLIGENT IN TUBINGEN, GERMANY, PROFESSOR FOR MACHINE LEA, MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS)
Elements of Causal Inference
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Mathematics for Machine Learning(2020) DEISENROTH, MARC PETER (UNIVERSITY COLLEGE LONDON),FAISAL, A. ALDO (IMPERIAL COLLEGE LONDON),ONG, CHENG SOONThis self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus73,49 €
DEISENROTH, MARC PETER (UNIVERSITY COLLEGE LONDON),FAISAL, A. ALDO (IMPERIAL COLLEGE LONDON),ONG, CHENG SOON
Mathematics for Machine Learning
This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus
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Data-Driven Science and Engineering(2022) BRUNTON, STEVEN L. (UNIVERSITY OF WASHINGTON),KUTZ, J. NATHAN (UNIVERSITY OF WASHINGTON)Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB®, new chapters on rein84,79 €
BRUNTON, STEVEN L. (UNIVERSITY OF WASHINGTON),KUTZ, J. NATHAN (UNIVERSITY OF WASHINGTON)
Data-Driven Science and Engineering
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB®, new chapters on rein
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First Course in Machine Learning(2020) ROGERS, SIMON,GIROLAMI, MARKThe new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Cla73,49 €
ROGERS, SIMON,GIROLAMI, MARK
First Course in Machine Learning
The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Cla
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Machine Learning for Signal Processing(2019) LITTLE, PROF MAX A. (PROFESSOR OF MATHEMATICS, ASTON UNIVERSITY, PROFESSOR OF MATHEMATICS, ASTON UNIVERSITY, ASTON UNIVERSITY, BIRMINGHAM)Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gra120,43 €
LITTLE, PROF MAX A. (PROFESSOR OF MATHEMATICS, ASTON UNIVERSITY, PROFESSOR OF MATHEMATICS, ASTON UNIVERSITY, ASTON UNIVERSITY, BIRMINGHAM)
Machine Learning for Signal Processing
Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gra
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