Fundamentals and methods of machine and deep learning, Singh, Pardeep
Автор: Saleh Hyatt Название: Machine Learning Fundamentals ISBN: 1789803551 ISBN-13(EAN): 9781789803556 Издательство: Неизвестно Рейтинг: Цена: 47810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains the scikit-learn API, which is a package created to facilitate the process of building machine learning applications. By explaining the differences between supervised and unsupervised models and by ...
Автор: Kaizhu Huang; Amir Hussain; Qiu-Feng Wang; Rui Zha Название: Deep Learning: Fundamentals, Theory and Applications ISBN: 3030060721 ISBN-13(EAN): 9783030060725 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications.
Автор: Alan H. Fielding Название: Machine Learning Methods for Ecological Applications ISBN: 1461374138 ISBN-13(EAN): 9781461374138 Издательство: Springer Рейтинг: Цена: 148020.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is the first text aimed at introducing machine learning methods to a readership of professional ecologists. All but one of the chapters have been written by ecologists and biologists who highlight the application of a particular method to a particular class of problem.
Автор: Isupova Название: Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video ISBN: 3319755072 ISBN-13(EAN): 9783319755076 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes.Behaviour analysis and anomaly detection are key components of intelligent vision systems.
Автор: Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis Название: Data Exploration Using Example-Based Methods ISBN: 1681734559 ISBN-13(EAN): 9781681734552 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: Data usually comes in a plethora of formats and dimensions, rendering the information extraction and exploration processes challenging. Thus, being able to perform exploratory analyses of the data with the intent of having an immediate glimpse of some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicated declarative languages (such as SQL) and mechanisms, while at the same time retaining the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or analyst, circumvents query languages by using examples as input. An example is a representative of the intended results or, in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind but may not be able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when they are performing a particularly challenging task like finding duplicate items, or when they are simply exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how different data types require different techniques and present algorithms that are specifically designed for relational, textual, and graph data. The book also presents the challenges and new frontiers of machine learning in online settings that have recently attracted the attention of the database community. The book concludes with a vision for further research and applications in this area.
Автор: Mathar Rudolf, Alirezaei Gholamreza, Balda Emilio Название: Fundamentals of Data Analytics: With a View to Machine Learning ISBN: 303056830X ISBN-13(EAN): 9783030568306 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces the basic methodologies for successful data analytics. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
Автор: Rigatos Gerasimos G. Название: State-Space Approaches for Modelling and Control in Financial Engineering: Systems Theory and Machine Learning Methods ISBN: 3319850040 ISBN-13(EAN): 9783319850047 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Systems theory and stability concepts.- Main approaches to nonlinear control.- Main approaches to nonlinear estimation.- Linearizing control and filtering for nonlinear dynamics in financial systems.- Nonlinear optimal control and filtering for financial systems.- Kalman Filtering Approach for detection of option mispricing inthe Black-Scholes PDE.- Kalman Filtering approach to the detection of option mispricing inelaborated PDE finance models.- Corporations' default probability forecasting using theDerivative-free nonlinear Kalman Filter.- Validation of financial options models using neural networks with invariance to Fourier transform.- Statistical validation of financial forecasting tools with generalized likelihood ratio approaches.- Distributed validation of option price forecasting tools using a statistical fault diagnosis approach.- Stabilization of financial systems dynamics through feedbackcontrol of the Black-Scholes PDE.- Stabilization of the multi-asset Black-Scholes PDE using differentialflatness theory.- Stabilization of commodities pricing PDE using differential flatnesstheory.- Stabilization of mortgage price dynamics using differential flatness theory.v>
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 76690.00 T Наличие на складе: Поставка под заказ. Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Автор: Vaughn Percy Название: Fundamentals of Machine Learning ISBN: 1635496799 ISBN-13(EAN): 9781635496796 Издательство: Неизвестно Цена: 163070.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Bender Emily M., Lascarides Alex Название: Linguistic Fundamentals for Natural Language Processing II: 100 Essentials from Semantics and Pragmatics ISBN: 1681736217 ISBN-13(EAN): 9781681736211 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 104410.00 T Наличие на складе: Поставка под заказ. Описание: Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG).
This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed by what is known about how humans use language to express and understand communicative intents. The purpose of this book is to present a selection of useful information about semantics and pragmatics, as understood in linguistics, in a way that's accessible to and useful for NLP practitioners with minimal (or even no) prior training in linguistics.
Автор: Trappenberg Thomas Название: Fundamentals of Machine Learning ISBN: 0198828047 ISBN-13(EAN): 9780198828044 Издательство: Oxford Academ Рейтинг: Цена: 43810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Interest in machine learning is exploding across the world, both in research and for industrial applications. Fundamentals of Machine Learning provides a brief and accessible introduction to this rapidly growing field, one that will appeal to both students and researchers.
This book constitutes the refereed post-conference proceedings of the 6th International Symposium on Computational Modeling of Objects Presented in Images, CompIMAGE 2018, held in Cracow, Poland, in
July 2018.
The 16 revised full papers presented in this book were carefully reviewed and selected from 30 submissions. The papers cover the following topics: digital geometry; digital tomography; and methods and applications.
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