Algorithmic Mathematics In Machine Learning
DOWNLOAD
Download Algorithmic Mathematics In Machine Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Algorithmic Mathematics In Machine Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Algorithmic Mathematics In Machine Learning
DOWNLOAD
Author : Bastian Bohn
language : en
Publisher: SIAM
Release Date : 2024-04-08
Algorithmic Mathematics In Machine Learning written by Bastian Bohn and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-08 with Computers categories.
This unique book explores several well-known machine learning and data analysis algorithms from a mathematical and programming perspective. The authors present machine learning methods, review the underlying mathematics, and provide programming exercises to deepen the reader’s understanding; accompany application areas with exercises that explore the unique characteristics of real-world data sets (e.g., image data for pedestrian detection, biological cell data); and provide new terminology and background information on mathematical concepts, as well as exercises, in “info-boxes” throughout the text. Algorithmic Mathematics in Machine Learning is intended for mathematicians, computer scientists, and practitioners who have a basic mathematical background in analysis and linear algebra but little or no knowledge of machine learning and related algorithms. Researchers in the natural sciences and engineers interested in acquiring the mathematics needed to apply the most popular machine learning algorithms will also find this book useful. This book is appropriate for a practical lab or basic lecture course on machine learning within a mathematics curriculum.
Algorithmic Mathematics In Machine Learning
DOWNLOAD
Author : Bastian Bohn (Mathematician)
language : en
Publisher:
Release Date : 2024
Algorithmic Mathematics In Machine Learning written by Bastian Bohn (Mathematician) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Machine learning categories.
"Explores several well-known machine learning and data analysis approaches from a mathematical perspective and also implements and applies the underlying algorithms to achieve a programming and practical perspective"--
Combinatorial And Algorithmic Mathematics
DOWNLOAD
Author : Baha Alzalg
language : en
Publisher: John Wiley & Sons
Release Date : 2024-07-31
Combinatorial And Algorithmic Mathematics written by Baha Alzalg and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Technology & Engineering categories.
Detailed review of optimization from first principles, supported by rigorous math and computer science explanations and various learning aids Supported by rigorous math and computer science foundations, Combinatorial and Algorithmic Mathematics: From Foundation to Optimization provides a from-scratch understanding to the field of optimization, discussing 70 algorithms with roughly 220 illustrative examples, 160 nontrivial end-of-chapter exercises with complete solutions to ensure readers can apply appropriate theories, principles, and concepts when required, and Matlab codes that solve some specific problems. This book helps readers to develop mathematical maturity, including skills such as handling increasingly abstract ideas, recognizing mathematical patterns, and generalizing from specific examples to broad concepts. Starting from first principles of mathematical logic, set-theoretic structures, and analytic and algebraic structures, this book covers both combinatorics and algorithms in separate sections, then brings the material together in a final section on optimization. This book focuses on topics essential for anyone wanting to develop and apply their understanding of optimization to areas such as data structures, algorithms, artificial intelligence, machine learning, data science, computer systems, networks, and computer security. Combinatorial and Algorithmic Mathematics includes discussion on: Propositional logic and predicate logic, set-theoretic structures such as sets, relations, and functions, and basic analytic and algebraic structures such as sequences, series, subspaces, convex structures, and polyhedra Recurrence-solving techniques, counting methods, permutations, combinations, arrangements of objects and sets, and graph basics and properties Asymptotic notations, techniques for analyzing algorithms, and computational complexity of various algorithms Linear optimization and its geometry and duality, simplex and non-simplex algorithms for linear optimization, second-order cone programming, and semidefinite programming Combinatorial and Algorithmic Mathematics is an ideal textbook resource on the subject for students studying discrete structures, combinatorics, algorithms, and optimization. It also caters to scientists across diverse disciplines that incorporate algorithms and academics and researchers who wish to better understand some modern optimization methodologies.
Algorithmic Learning In A Random World
DOWNLOAD
Author : Vladimir Vovk
language : en
Publisher: Springer Nature
Release Date : 2022-12-13
Algorithmic Learning In A Random World written by Vladimir Vovk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-13 with Computers categories.
This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature of conformal prediction is the principled treatment of the reliability of predictions. The prediction algorithms described — conformal predictors — are provably valid in the sense that they evaluate the reliability of their own predictions in a way that is neither over-pessimistic nor over-optimistic (the latter being especially dangerous). The approach is still flexible enough to incorporate most of the existing powerful methods of machine learning. The book covers both key conformal predictors and the mathematical analysis of their properties. Algorithmic Learning in a Random World contains, in addition to proofs of validity, results about the efficiency of conformal predictors. The only assumption required for validity is that of "randomness" (the prediction algorithm is presented with independent and identically distributed examples); in later chapters, even the assumption of randomness is significantly relaxed. Interesting results about efficiency are established both under randomness and under stronger assumptions. Since publication of the First Edition in 2005 conformal prediction has found numerous applications in medicine and industry, and is becoming a popular machine-learning technique. This Second Edition contains three new chapters. One is about conformal predictive distributions, which are more informative than the set predictions produced by standard conformal predictors. Another is about the efficiency of ways of testing the assumption of randomness based on conformal prediction. The third new chapter harnesses conformal testing procedures for protecting machine-learning algorithms against changes in the distribution of the data. In addition, the existing chapters have been revised, updated, and expanded.
Machine Learning Math
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2020-05-21
Machine Learning Math written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-21 with categories.
Are you looking for a complete guide of machine learning? Then keep reading... In this book, you will learn about the OpenAI Gym, used in reinforcement learning projects with several examples of the training platform provided out of the box. Machine Learning Math is the book most readers will want to have when starting to learn machine learning. This book is a reference, something you can keep coming back to hence suitable for newbies. The book is perfect for all people who have a desire to study data science. Have you heard of machine learning being everywhere, and you intend to understand what it can do? Or are you familiar with applying the tools of machine learning, but you want to make sure you aren't missing any? Having a little knowledge about mathematics, statistics, and probability would be helpful, but this book has been written in such a way that you will get most of this knowledge as you continue reading. You should not shy away from reading the book if you have no background in machine learning. You will learn how to use reinforcement learning algorithms in other tasks, for example, the board game Go, and generating deep image classifiers. This will help you to get a comprehensive understanding of reinforcement learning and help you solve real-world problems. The most interesting part of this book is the asynchronous reinforcement learning framework. You will learn what the shortcomings of DQN are, and why DQN is challenging to apply in complex tasks. Then, you will learn how to apply the asynchronous reinforcement learning framework in the actor-critic method REINFORCE, which led us to the A3C algorithm. You will learn four important things. The first one is how to implement games using gym and how to play games for relaxation and having fun. The second one is that you will learn how to preprocess data in reinforcement learning tasks such as in computer games. For practical machine learning applications, you will spend a great deal of time understanding and refining data, which affects the performance of an AI system a lot. The third one is the deep Q-learning algorithm. You will learn the intuition behind it, for example, why the replay memory is necessary, why the target network is needed, where the update rule comes from, and so on. The final one is that you will learn how to implement DQN using TensorFlow and how to visualize the training process. The following is a glimpse of what you will find inside the book: Introduction to machine learning The best machine learning algorithms Regression (a problem of predicting a real-valued label) and classification( a problem of automatically assigning a label to unlabeled example-for example spam detection) Reinforcement learning Robotics Supervised and Unsupervised learning How to implement a convolutional neural network(usually used for images) in TensorFlow Deep Learning Data preparation and processing TensorFlow machine learning frameworks Neural Networks (a combination of linear and non-linear functions) Clustering(aims to group similar samples together) Even if you have never studied Machine Learning before, you can learn it quickly. So what are you waiting for? Go to the top of the page and click Buy Now!
Intelligent Computer Mathematics
DOWNLOAD
Author : Florian Rabe
language : en
Publisher: Springer
Release Date : 2018-08-02
Intelligent Computer Mathematics written by Florian Rabe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-02 with Computers categories.
This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Computer Mathematics, CICM 2018, held in Hagenberg, Austria, in August 2018. The 23 full papers presented were carefully reviewed and selected from a total of 36 submissions. The papers focos on the Calculemus, Digital Mathematics Libraries, and Mathematical Knowledge Management tracks which also correspond to the subject areas of the predecessor meetings. Orthogonally, the Systems and Projects track called for descriptions of digital resources, such as data and systems, and of projects, whether old, current, or new, and survey papers covering any topics of relevance to the CICM community.
Machine Learning
DOWNLOAD
Author : Stephen Marsland
language : en
Publisher: CRC Press
Release Date : 2014-10-08
Machine Learning written by Stephen Marsland and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-08 with Business & Economics categories.
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince 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
Simulation And Analysis Of Mathematical Methods In Real Time Engineering Applications
DOWNLOAD
Author : T. Ananth Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-08
Simulation And Analysis Of Mathematical Methods In Real Time Engineering Applications written by T. Ananth Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-08 with Mathematics categories.
SIMULATIONS AND ANALYSIS of Mathematical Methods Written and edited by a group of international experts in the field, this exciting new volume covers the state of the art of real-time applications of computer science using mathematics. This breakthrough edited volume highlights the security, privacy, artificial intelligence, and practical approaches needed by engineers and scientists in all fields of science and technology. It highlights the current research, which is intended to advance not only mathematics but all areas of science, research, and development, and where these disciplines intersect. As the book is focused on emerging concepts in machine learning and artificial intelligence algorithmic approaches and soft computing techniques, it is an invaluable tool for researchers, academicians, data scientists, and technology developers. The newest and most comprehensive volume in the area of mathematical methods for use in real-time engineering, this groundbreaking new work is a must-have for any engineer or scientist’s library. Also useful as a textbook for the student, it is a valuable contribution to the advancement of the science, both a working handbook for the new hire or student, and a reference for the veteran engineer.
Algorithmic Learning Theory
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1999
Algorithmic Learning Theory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computer algorithms categories.
Algorithmic Learning
DOWNLOAD
Author : Alan Hutchinson
language : en
Publisher: Oxford University Press, USA
Release Date : 1994
Algorithmic Learning written by Alan Hutchinson and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
Machine learning is a rapidly changing field within artificial intelligence, as more algorithms are identified and a theory of which algorithm will suit which purpose emerges. Artificial Learning provides a comprehensive introduction to all aspects of the subject and will be both aninvaluable text for students and a reference for practitioners seeking an up-to-date review.