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Machine Learning Mit Python


Author : Sebastian Raschka
language : de
Publisher: MITP-Verlags GmbH & Co. KG
Release Date : 2016-11-22



Download Machine Learning Mit Python written by Sebastian Raschka and has been published by MITP-Verlags GmbH & Co. KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-22 with Computers categories.




Statistical Reinforcement Learning


Author : Masashi Sugiyama
language : en
Publisher: CRC Press
Release Date : 2015-03-16



Download Statistical Reinforcement Learning written by Masashi Sugiyama and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-16 with Business & Economics categories.


Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence, plant control, and gaming, the RL framework is ideal for decision making in unknown environments with large amounts of data. Supplying an up-to-date and accessible introduction to the field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms of statistical reinforcement learning from the modern machine learning viewpoint. It covers various types of RL approaches, including model-based and model-free approaches, policy iteration, and policy search methods. Covers the range of reinforcement learning algorithms from a modern perspective Lays out the associated optimization problems for each reinforcement learning scenario covered Provides thought-provoking statistical treatment of reinforcement learning algorithms The book covers approaches recently introduced in the data mining and machine learning fields to provide a systematic bridge between RL and data mining/machine learning researchers. It presents state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RL. Numerous illustrative examples are included to help readers understand the intuition and usefulness of reinforcement learning techniques. This book is an ideal resource for graduate-level students in computer science and applied statistics programs, as well as researchers and engineers in related fields.

K Nstliche Intelligenz


Author : Stuart J. Russell
language : en
Publisher:
Release Date : 2004



Download K Nstliche Intelligenz written by Stuart J. Russell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.




Introduction To Machine Learning


Author : Ethem Alpaydin
language : en
Publisher: MIT Press
Release Date : 2014-08-29



Download Introduction To Machine Learning written by Ethem Alpaydin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-29 with Computers categories.


The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.

Data Mining


Author : Ian H. Witten
language : en
Publisher: Morgan Kaufmann
Release Date : 2000



Download Data Mining written by Ian H. Witten and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.


This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large collections of data. Complementing the book's instruction is fully functional machine learning software.

Einf Hrung In Python


Author : Mark Lutz
language : de
Publisher: O'Reilly Germany
Release Date : 2007



Download Einf Hrung In Python written by Mark Lutz and has been published by O'Reilly Germany this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Python (Computer program language) categories.




Das Geheimnis Des Menschlichen Denkens


Author : Ray Kurzweil
language : de
Publisher: Lola Books
Release Date : 2015-07-31



Download Das Geheimnis Des Menschlichen Denkens written by Ray Kurzweil and has been published by Lola Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-31 with Science categories.


Der Wettlauf um das Gehirn hat begonnen. Sowohl die EU als auch die USA haben gewaltige Forschungsprojekte ins Leben gerufen um das Geheimnis des menschlichen Denkens zu entschlüsseln. 2023 soll es dann soweit sein: Das menschliche Gehirn kann vollständig simuliert werden. In "Das Geheimnis des menschlichen Denkens" gewährt Googles Chefingenieur Ray Kurzweil einen spannenden Einblick in das Reverse Engineering des Gehirns. Er legt dar, wie mithilfe der Mustererkennungstheorie des Geistes der ungeheuren Komplexität des Gehirns beizukommen ist und wirft einen ebenso präzisen wie überraschenden Blick auf die am Horizont sich bereits abzeichnende Zukunft. Ist das menschliche Gehirn erst einmal simuliert, wird künstliche Intelligenz die Fähigkeiten des Menschen schon bald übertreffen. Ein Ereignis, das Kurzweil aufgrund der bereits in "Menschheit 2.0" entworfenen exponentiellen Wachstumskurve der Informationstechnologien bereits für das Jahr 2029 prognostiziert. Aber was dann? Kurzweil ist zuversichtlich, dass die Vorteile künstlicher Intelligenz mögliche Bedrohungsszenarien überwiegen und sie uns entscheidend dabei hilft, uns weiterzuentwickeln und die Herausforderungen der Zukunft zu meistern.