This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer

優惠價： 9 3038

無庫存

42.

Beginning Julia Programming ― For Engineers and Scientists

出版日：2017/11/27 作者：Sandeep Nagar 出版社：Apress 裝訂：平裝

Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionalit

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

43.

Reactive Machine Learning Systems

出版日：2017/10/31 作者：Jeff Smith 出版社：Manning Pubns Co 裝訂：平裝

Machine learning applications autonomously reason about data at massive scale. It's important that they remain responsive in the face of failure and changes in load. But machine learning systems are d

優惠價： 1 2250

無庫存

MATLAB Deep Learning ─ With Machine Learning, Neural Networks and Artificial Intelligence

滿額折

44.

MATLAB Deep Learning ─ With Machine Learning, Neural Networks and Artificial Intelligence

出版日：2017/07/06 作者：Phil Kim 出版社：Apress 裝訂：平裝

Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolu

優惠價： 1 3769

無庫存

45.

Machine Learning and Medical Imaging

出版日：2016/08/19 作者：Guorong Wu; Dinggang Shen 出版社：Academic Pr 裝訂：精裝

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, inc

優惠價： 1 4338

無庫存

滿額折

46.

Machine Learning for Dummies

出版日：2016/06/07 作者：John Paul Mueller; Luca Massaron 出版社：For Dummies 裝訂：平裝

Machine learning is an exciting new way to use computers to perform tasks that require the ability to learn from experience. In order to make machine learning a reality, programmers rely on special la

優惠價： 9 1026

無庫存

Financial Signal Processing And Machine Learning

90 折

47.

Financial Signal Processing And Machine Learning

出版日：2016/04/14 作者：Akansu 出版社：John Wiley & Sons Inc 裝訂：精裝

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available.Financial Signal Processing and Machine

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

48.

Real-world Machine Learning

出版日：2016/03/02 作者：Henrik Brink; Joseph Richards; Mark Fetherolf 出版社：Oreilly & Associates Inc 裝訂：平裝

In a world where big data is the norm and near-real-time decisions are crucial, machine learning (ML) is a critical component of the data workflow. Machine learning systems can quickly crunch massive

優惠價： 1 2500

無庫存

49.

Practical Machine Learning

出版日：2016/01/31 出版社：Packt Pub Ltd 裝訂：平裝

Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniquesAbout This BookFully-coded working examples using a wide range of machine learning libraries and

優惠價： 1 2939

無庫存

50.

Machine Learning Models and Algorithms for Big Data Classification ― Thinking With Examples for Effective Learning

出版日：2015/10/21 作者：Shan Suthaharan 出版社：Springer Verlag 裝訂：精裝

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random for

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

51.

Python Machine Learning

出版日：2015/09/23 作者：Sebastian Raschka 出版社：Packt Pub Ltd 裝訂：平裝

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wr

優惠價： 1 2819

無庫存

52.

A Primer for Financial Engineering ― Financial Signal Processing and Electronic Trading

出版日：2015/03/25 作者：Ali N. Akansu; Mustafa U. Torun 出版社：Elsevier Science Ltd 裝訂：平裝

This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial market

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

79 折

53.

Introduction to Machine Learning

出版日：2014/08/22 作者：Ethem Alpaydin 出版社：Mit Pr 裝訂：精裝

The goal of machine learning is to program computers to use example data or pastexperience to solve a given problem. Many successful applications of machine learning exist already,including systems th

到貨時通知我

Understanding Machine Learning ― From Theory to Algorithms

滿額折

54.

Understanding Machine Learning ― From Theory to Algorithms

出版日：2014/05/31 作者：Shai Shalev-Shwartz 出版社：Cambridge Univ Pr 裝訂：精裝

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible t

優惠價： 9 2807

無庫存

Statistical Inference for Financial Engineering

90 折

55.

Statistical Inference for Financial Engineering

出版日：2014/05/03 作者：Masanobu Taniguchi; Tomoyuki Amano; Hiroaki Ogata; Hiroyuki Taniai 出版社：Springer Verlag 裝訂：平裝

?This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial time series data. In order to describe th

優惠價： 9 2835

無庫存

56.

LEARNING FROM DATA

出版日：2012/11/01 作者：HSUAN -TIEN LIN(NTU) 出版社：AML BOOK 裝訂：精裝

Machine learning allows computational systems to adaptively improve their performance with experience accumulated from the observed data. Its techniques are widely applied in engineering, science, fin

到貨時通知我

57.

Machine Learning in Action

出版日：2012/04/16 作者：Peter Harrington 出版社：Oreilly & Associates Inc 裝訂：平裝

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the fle

優惠價： 1 2250

無庫存

90 折

58.

Scaling Up Machine Learning

出版日：2011/12/30 作者：Ron Bekkerman 出版社：Cambridge Univ Pr 裝訂：精裝

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

59.

Machine Learning and Data Mining for Computer Security

出版日：2011/12/16 作者：Marcus A. Maloof 出版社：Springer-Verlag New York Inc 裝訂：平裝

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

79 折

60.

Optimization for Machine Learning

出版日：2011/09/30 作者：Suvrit Sra; Sebastian Nowozin; Stephen J. Wright; Suvrit Sra 出版社：Mit Pr 裝訂：平裝

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning

到貨時通知我

Data Mining ─ Practical Machine Learning Tools and Techniques

90 折

61.

Data Mining ─ Practical Machine Learning Tools and Techniques

出版日：2011/01/04 作者：Ian H. Witten; Eibe Frank; Geoffrey Holmes 出版社：新月圖書 裝訂：平裝

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in r

優惠價： 9 1125

無庫存

62.

Mathematics for Finance: An Introduction to Financial Engineering

出版日：2010/11/29 作者：Marek Capinski; Tomasz Zastawniak 出版社：Springer Verlag 裝訂：平裝

As with the first edition, Mathematics for Finance: An Introduction to Financial Engineering combines financial motivation with mathematical style. Assuming only basic knowledge of probability and cal

優惠價： 1 2498

無庫存

滿額折

63.

Thermal Deformation in Machine Tools

出版日：2010/06/21 作者：ITO 出版社：Mcgraw-Hill; Inc. 裝訂：精裝

Proven guidelines for reducing thermal deformation in machine tools Written by global experts in the field of machine tool engineering, this authoritative work offers tested solutions for reducing the

優惠價： 79 3358

無庫存

79 折

64.

Introduction to Machine Learning

出版日：2009/12/04 作者：Ethem Alpaydin 出版社：Mit Pr 裝訂：精裝

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

到貨時通知我

90 折

65.

Machine Learning In Bioinformatics

出版日：2008/11/13 作者：Zhang 出版社：John Wiley & Sons Inc 裝訂：精裝

An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology a

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

66.

Ontology Learning and Population: Bridging the Gap Between Text and Knowledge

出版日：2008/08/30 作者：Paul Buitelaar (EDT); Philipp Cimiano (EDT) 出版社：Ios Pr Inc 裝訂：精裝

Contributors from natural language processing, machine learning, knowledge representation and engineering, and user interface design explore theories and practices by which people can learn simply by

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

67.

Machine Learning And Data Mining for Computer Security

出版日：2005/09/27 作者：Marcus A. Maloof (EDT) 出版社：Springer-Verlag New York Inc 裝訂：精裝

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

79 折

68.

Introduction To Machine Learning

出版日：2004/10/15 作者：Ethem Alpaydin 出版社：Mit Pr 裝訂：精裝

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

到貨時通知我

69.

Machine Learning ─ Discriminative and Generative

出版日：2003/11/01 作者：Tony Jebara 出版社：Kluwer Academic Pub 裝訂：精裝

Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines.

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

Financial Engineering and Computation：Principles, Mathematics, Algorithms

90 折

70.

Financial Engineering and Computation：Principles, Mathematics, Algorithms

出版日：2001/11/12 作者：Yuh-Dauh Lyuu 出版社：Cambridge Univ Pr 裝訂：精裝

Students and professionals intending to work in any area of finance must master not only advanced concepts and mathematical models but also learn how to implement these models computationally. This comprehensive text, first published in 2002, combines the theory and mathematics behind financial engineering with an emphasis on computation, in keeping with the way financial engineering is practised in capital markets. Unlike most books on investments, financial engineering, or derivative securities, the book starts from very basic ideas in finance and gradually builds up the theory. It offers a thorough grounding in the subject for MBAs in finance, students of engineering and sciences who are pursuing a career in finance, researchers in computational finance, system analysts, and financial engineers. Along with the theory, the author presents numerous algorithms for pricing, risk management, and portfolio management. The emphasis is on pricing financial and derivative securities: bonds,

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

滿額折

71.

Personalized Machine Learning

出版日：2022/01/31 作者：Julian McAuley 出版社：Cambridge Univ Pr 裝訂：精裝

Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design mod

優惠價： 9 2339

無庫存

Quantum Machine Learning: An Applied Approach: The Theory and Application of Quantum Machine Learning in Science and Industry

滿額折

72.

Quantum Machine Learning: An Applied Approach: The Theory and Application of Quantum Machine Learning in Science and Industry

出版日：2021/08/24 作者：Santanu Ganguly 出版社：Apress 裝訂：平裝

Know how to adapt quantum computing and machine learning algorithms. This book takes you on a journey into hands-on quantum machine learning (QML) through various options available in industry and res

優惠價： 1 2660

無庫存

Machine Learning, revised and updated edition

滿額折

73.

Machine Learning, revised and updated edition

出版日：2021/08/17 作者：Ethem Alpaydin 出版社：Mit Pr 裝訂：平裝

A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.Today, machine learning underlies a range of app

優惠價： 79 479

無庫存

Machine Learning and Data Science in the Oil and Gas Industry：Best Practices, Tools, and Case Studies

90 折

74.

Machine Learning and Data Science in the Oil and Gas Industry：Best Practices, Tools, and Case Studies

出版日：2021/03/01 作者：Bangert; Patrick (Vice President of Artificial Intelligence at Samsung SDS; and Founder and Board Chair of Algorithmica Technologies; Cupertino; California; USA) 出版社：Elsevier Science Health Science div 裝訂：平裝

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure.Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

Detecting Regime Change in Computational Finance

90 折

75.

Detecting Regime Change in Computational Finance

出版日：2020/09/17 作者：Jun Chen and Edward P K Tsang 出版社：Chapman & Hall 裝訂：精裝

Based on interdisciplinary research into 'Directional Change', a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi

90 折

76.

Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi

出版日：2020/08/17 作者：Shrirang Ambaji Kulkarni; Varadrah P. Gurupur and Steven L. Fernandes 出版社：Chapman & Hall 裝訂：平裝

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

優惠價： 9 2749

無庫存

Introduction to Computer Vision, Machine Learning, and Deep Learning Applications using Raspberry Pi

90 折

77.

Introduction to Computer Vision, Machine Learning, and Deep Learning Applications using Raspberry Pi

出版日：2020/08/17 作者：Shrirang Ambaji Kulkarni; Varadrah P. Gurupur and Steven L. Fernandes 出版社：Chapman & Hall 裝訂：精裝

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

若需訂購本書，請電洽客服 02-25006600[分機130、131]。

90 折

78.

Neural Machine Translation

出版日：2020/06/30 作者：Philipp Koehn 出版社：Cambridge Univ Pr 裝訂：精裝

Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.

優惠價： 9 3293

無庫存

Data Mining and Machine Learning ― Fundamental Concepts and Algorithms

90 折

79.

Data Mining and Machine Learning ― Fundamental Concepts and Algorithms

出版日：2020/02/29 作者：Mohammed J. Zaki 出版社：Cambridge Univ Pr 裝訂：精裝

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.

優惠價： 9 3288

無庫存

Machine Learning With Spark And Python - Essential Techniques For Predictive Analytics

滿額折

80.

Machine Learning With Spark And Python - Essential Techniques For Predictive Analytics

出版日：2019/10/18 作者：Bowles 出版社：John Wiley & Sons Inc 裝訂：平裝

Machine Learning with Spark and Python Essential Techniques for Predictive Analytics Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves

優惠價： 9 1710

無庫存

共 566777筆

第 14170 頁
1
2
3
4
5
6
7
8
9
14170

熱搜：

Machine Learning for Financial Engineering

Machine-learning Techniques in Economics ― New Tools for Predicting Economic Growth

Beginning Julia Programming ― For Engineers and Scientists

Reactive Machine Learning Systems

MATLAB Deep Learning ─ With Machine Learning, Neural Networks and Artificial Intelligence

Machine Learning and Medical Imaging

Machine Learning for Dummies

Financial Signal Processing And Machine Learning

Real-world Machine Learning

Practical Machine Learning

Machine Learning Models and Algorithms for Big Data Classification ― Thinking With Examples for Effective Learning

Python Machine Learning

A Primer for Financial Engineering ― Financial Signal Processing and Electronic Trading

Introduction to Machine Learning

Understanding Machine Learning ― From Theory to Algorithms

Statistical Inference for Financial Engineering

LEARNING FROM DATA

Machine Learning in Action

Scaling Up Machine Learning

Machine Learning and Data Mining for Computer Security

Optimization for Machine Learning

Data Mining ─ Practical Machine Learning Tools and Techniques

Mathematics for Finance: An Introduction to Financial Engineering

Thermal Deformation in Machine Tools

Introduction to Machine Learning

Machine Learning In Bioinformatics

Ontology Learning and Population: Bridging the Gap Between Text and Knowledge

Machine Learning And Data Mining for Computer Security

Introduction To Machine Learning

Machine Learning ─ Discriminative and Generative

Financial Engineering and Computation：Principles, Mathematics, Algorithms

Personalized Machine Learning

Quantum Machine Learning: An Applied Approach: The Theory and Application of Quantum Machine Learning in Science and Industry

Machine Learning, revised and updated edition

Machine Learning and Data Science in the Oil and Gas Industry：Best Practices, Tools, and Case Studies

Detecting Regime Change in Computational Finance

Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi

Introduction to Computer Vision, Machine Learning, and Deep Learning Applications using Raspberry Pi

Neural Machine Translation

Data Mining and Machine Learning ― Fundamental Concepts and Algorithms

Machine Learning With Spark And Python - Essential Techniques For Predictive Analytics