Machine Learning Applications In Software Engineering

Industrial Applications of Machine Learning

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Industrial Applications of Machine Learning

出版日：2018/12/10 作者：Pedro Larrañaga; Alberto Ogbechie; Javier Diaz-rozo; David Atienza; Concha Bielza 出版社：CRC Pr I Llc 裝訂：精裝

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools

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Density Ratio Estimation in Machine Learning

90 折

2.

Density Ratio Estimation in Machine Learning

出版日：2018/03/29 作者：Masashi Sugiyama 出版社：Cambridge Univ Pr 裝訂：平裝

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

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Machine Learning In The Aws Cloud

出版日：2019/08/23 作者：Mishra 出版社：John Wiley & Sons Inc 裝訂：平裝

Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabiliti

優惠價： 9 1710

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Software Engineering Research, Management and Applications

90 折

4.

Software Engineering Research, Management and Applications

出版日：2019/07/10 作者：Roger Lee (EDT) 出版社：Springer Nature 裝訂：平裝

This book gathers 12 of the most promising papers presented at the 15th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2017) held

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Data Management in Machine Learning Systems

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5.

Data Management in Machine Learning Systems

出版日：2019/02/25 作者：Matthias Boehm; Arun Kumar; Jun Yang; H. V. Jagadish (EDT) 出版社：Morgan & Claypool 裝訂：平裝

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scala

優惠價： 1 3767

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6.

Artificial Intelligence and Machine Learning Fundamentals

出版日：2018/12/12 作者：Zsolt Nagy 出版社：Packt Pub Ltd 裝訂：平裝

Create AI applications in Python and lay the foundations for your career in data scienceKey FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail wit

優惠價： 1 1859

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Machine Learning: The Ultimate Guide to Machine Learning, Neural Networks and Deep Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

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Machine Learning: The Ultimate Guide to Machine Learning, Neural Networks and Deep Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

出版日：2018/10/10 作者：Herbert Jones 出版社：Createspace Independent Pub 裝訂：平裝

3 comprehensive manuscripts in 1 bookMachine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

優惠價： 1 792

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Software Languages ― Syntax, Semantics, and Metaprogramming

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8.

Software Languages ― Syntax, Semantics, and Metaprogramming

出版日：2018/05/28 作者：Ralf L鄝mel 出版社：Springer-Verlag New York Inc 裝訂：精裝

This book identifies, defines and illustrates the fundamental concepts and engineering techniques relevant to applications of software languages in software development. It presents software languages

優惠價： 9 3443

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Machine Learning: A Concise Introduction

90 折

9.

Machine Learning: A Concise Introduction

出版日：2018/03/30 作者：Knox 出版社：John Wiley & Sons Inc 裝訂：精裝

An introduction to machine learning that includes the fundamental techniques, methods, and applications Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concept

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The International Conference on Advanced Machine Learning Technologies and Applications (Amlta2018)

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10.

The International Conference on Advanced Machine Learning Technologies and Applications (Amlta2018)

出版日：2018/03/07 作者：Aboul Ella Hassanien (EDT); Mohamed F. Tolba (EDT); Mohamed Elhoseny (EDT); Mohamed Mostafa (EDT) 出版社：Springer-Verlag New York Inc 裝訂：平裝

This book presents the refereed proceedings of the third International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2018, held in Cairo, Egypt, on February 22–24, 2018,

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11.

Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

出版日：2018/01/31 作者：Md. Rezaul Karim 出版社：Packt Pub Ltd 裝訂：平裝

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.Key FeaturesExplore machine learning techniques with prominent ope

優惠價： 1 2819

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Data-driven Science and Engineering ― Machine Learning, Dynamical Systems, and Control

90 折

12.

Data-driven Science and Engineering ― Machine Learning, Dynamical Systems, and Control

出版日：2019/03/31 作者：Steven Brunton; J. Nathan Kutz 出版社：Cambridge Univ Pr 裝訂：精裝

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to

優惠價： 9 3041

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Ensemble Classification Methods With Applications In R

90 折

13.

Ensemble Classification Methods With Applications In R

出版日：2018/09/05 作者：Alfaro 出版社：John Wiley & Sons Inc 裝訂：精裝

An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts a

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14.

Essentials of Software Engineering

出版日：2018/05/24 作者：Theodore Hammond (EDT) 出版社：Clanrye Intl 裝訂：精裝

Software engineering refers to the process of applying engineering principles to develop software in a systematic method. It includes developing, designing, researching, operating and compiling system

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Machine Learning and Security ─ Protecting Systems With Data and Algorithms

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15.

Machine Learning and Security ─ Protecting Systems With Data and Algorithms

出版日：2018/01/13 作者：Clarence Chio; David Freeman 出版社：Oreilly & Associates Inc 裝訂：平裝

Machine learning has become a hot topic in computer security in the past couple of years as a technique that can counter advances in attacker competency. This book will provide security and software p

優惠價： 1 3629

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Handbook of Machine Learning ― Optimization and Decision Making

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16.

Handbook of Machine Learning ― Optimization and Decision Making

出版日：2019/10/29 作者：Collins Achepsah Leke; Tshilidzi Marwala 出版社：World Scientific Publishing Co Pte Ltd 裝訂：精裝

Building on Handbook of Machine Learning - Volume 1: Foundation of Artificial Intelligence, this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like th

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Big Data And Machine Learning In Quantitative Investment

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17.

Big Data And Machine Learning In Quantitative Investment

出版日：2019/02/07 作者：Guida 出版社：John Wiley & Sons Inc 裝訂：精裝

Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investmentBig Data and Machine Learning in Quantitative Investment is not just about demonstrat

優惠價： 9 1778

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Deep Learning Illustrated ― A Visual, Interactive Guide to Artificial Intelligence

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Deep Learning Illustrated ― A Visual, Interactive Guide to Artificial Intelligence

出版日：2018/12/14 作者：Jon Krohn; Beyleveld Grant; Agla? Bassens 出版社：Addison-Wesley Professional 裝訂：平裝

Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Googl

優惠價： 1 2880

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Machine Learning with Python: A Step-By-Step Guide to Learn and Master Python Machine Learning

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Machine Learning with Python: A Step-By-Step Guide to Learn and Master Python Machine Learning

出版日：2018/11/23 作者：Mr Hein Smith 出版社：Createspace Independent Pub 裝訂：平裝

Are you stuck in getting started with machine learning with python? A Step-By-Step Guide to Learn and Master Python Machine Learning walks you through steps for getting started with Machine Learning w

優惠價： 1 834

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Advanced Applications in Manufacturing Engineering

90 折

20.

Advanced Applications in Manufacturing Engineering

出版日：2018/11/09 作者：Mangey Ram (EDT); J. Paulo Davim (EDT) 出版社：Woodhead Pub Ltd 裝訂：平裝

Advanced Applications in Manufacturing Engineering presents the latest research and development in manufacturing engineering across a range of areas, treating manufacturing engineering on an internati

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90 折

21.

Source Separation and Machine Learning

出版日：2018/11/01 作者：Jen-tzung Chien 出版社：Academic Pr 裝訂：平裝

Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It il

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Solving Partial Differential Equation Applications With Pde2D

90 折

22.

Solving Partial Differential Equation Applications With Pde2D

出版日：2018/09/21 作者：Sewell 出版社：John Wiley & Sons Inc 裝訂：精裝

Solve engineering and scientific partial differential equation applications using the PDE2D software developed by the author Solving Partial Differential Equation Applications with PDE2D derives

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Optimization Techniques And Applications With Examples

90 折

23.

Optimization Techniques And Applications With Examples

出版日：2018/09/07 作者：Yang 出版社：John Wiley & Sons Inc 裝訂：精裝

A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techn

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Deep Learning for Nlp and Speech Recognition

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24.

Deep Learning for Nlp and Speech Recognition

出版日：2019/06/24 作者：Uday Kamath; John Liu; Jimmy Whitaker 出版社：Springer-Verlag New York Inc 裝訂：精裝

This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the w

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Practical Machine Learning and Image Processing ― For Facial Recognition, Object Detection, and Pattern Recognition Using Python

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25.

Practical Machine Learning and Image Processing ― For Facial Recognition, Object Detection, and Pattern Recognition Using Python

出版日：2019/03/01 作者：Himanshu Singh 出版社：Apress 裝訂：平裝

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

優惠價： 1 2470

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26.

Multiview Machine Learning

出版日：2019/01/17 作者：Shiliang Sun; Liang Mao; Ziang Dong; Lidan Wu 出版社：Springer-Nature New York Inc 裝訂：精裝

This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpin

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Machine Learning Using R ― With Time Series and Industry-based Use Cases in R

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27.

Machine Learning Using R ― With Time Series and Industry-based Use Cases in R

出版日：2019/01/04 作者：Karthik Ramasubramanian; Abhishek Singh 出版社：Apress 裝訂：平裝

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use i

優惠價： 1 2660

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79 折

28.

Foundations of Machine Learning

出版日：2018/12/25 作者：Mehryar Mohri; Afshin Rostamizadeh; Ameet Talwalkar; Francis Bach 出版社：Mit Pr 裝訂：精裝

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.This book is a general introduction to machine learning that can serve as a textbook f

優惠價： 79 4029

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90 折

29.

Algorithmic Aspects of Machine Learning

出版日：2018/07/31 作者：Ankur Moitra 出版社：Cambridge Univ Pr 裝訂：精裝

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

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30.

Algorithmic Aspects of Machine Learning

出版日：2018/07/31 作者：Ankur Moitra 出版社：Cambridge Univ Pr 裝訂：平裝

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

優惠價： 9 1520

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Deep Learning Cookbook ― Practical Rrecipes to Get Started Quickly

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Deep Learning Cookbook ― Practical Rrecipes to Get Started Quickly

出版日：2018/06/25 作者：Douwe Osinga 出版社：Oreilly & Associates Inc 裝訂：平裝

Recent developments in deep learning have put the field center stage for innovation in software engineering. New algorithms and techniques in academia hold promise for many real world problems, and ne

優惠價： 1 3299

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Human and Machine Learning ― Visible, Explainable, Trustworthy and Transparent

90 折

32.

Human and Machine Learning ― Visible, Explainable, Trustworthy and Transparent

出版日：2018/06/20 作者：Jianlong Zhou (EDT); Fang Chen (EDT) 出版社：Springer-Verlag New York Inc 裝訂：精裝

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different ap

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90 折

33.

The Essence of Software Engineering

出版日：2018/06/10 作者：Volker Gruhn (EDT); Riger Striemer (EDT) 出版社：Springer-Nature New York Inc 裝訂：精裝

This open access book includes contributions by leading researchers and industry thought leaders on various topics related to the essence of software engineering and their application in industrial pr

優惠價： 9 2430

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Advances in Machine Learning and Data Science ― Recent Achievements and Research Directives

90 折

34.

Advances in Machine Learning and Data Science ― Recent Achievements and Research Directives

出版日：2018/05/17 作者：Damodar Reddy (EDT); Pawan Lingras (EDT); Venkatanareshbabu Kuppili (EDT) 出版社：Springer-Verlag New York Inc 裝訂：平裝

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine

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Introduction to Machine Learning With R ― Rigorous Mathematical Analysis

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35.

Introduction to Machine Learning With R ― Rigorous Mathematical Analysis

出版日：2018/03/25 作者：Scott V. Burger 出版社：Oreilly & Associates Inc 裝訂：平裝

Machine learning can be a difficult subject if you’re not familiar with the basics. With this book, you'll get a solid foundation of introductory principles used in machine learning with the sta

優惠價： 1 3079

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36.

Data Intensive Computing Applications for Big Data

出版日：2018/02/28 作者：M. Mittal (EDT); R. Kumar (EDT); D. J. Hemanth (EDT); V. E. Balas (EDT) 出版社：Ios Pr Inc 裝訂：平裝

The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing par

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Engineering Analysis With Ansys Software

90 折

37.

Engineering Analysis With Ansys Software

出版日：2018/01/10 作者：Tadeusz Stolarski; Yuji Nakasone; Shigeka Yoshimoto 出版社：Butterworth-Heinemann 裝訂：平裝

Engineering Analysis with ANSYS Software, Second Edition, provides a comprehensive introduction to fundamental areas of engineering analysis needed for research or commercial engineering projects. The

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90 折

38.

Rock Mechanics and Rock Engineering

出版日：2019/12/27 作者：Ömer Aydan 出版社：CRC Press UK 裝訂：精裝

Volume 2, Applications of Rock Mechanics – Rock Engineering, discusses the applications of rock mechanics to engineering structures in/on rock, rock excavation techniques and in-situ monitoring techni

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Theories of Human Learning ― Mrs Gribbin's Cat

90 折

39.

Theories of Human Learning ― Mrs Gribbin's Cat

出版日：2019/11/30 作者：Guy R. Lefrançois 出版社：Cambridge Univ Pr 裝訂：精裝

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and applications in all areas. It presents a comprehensive view of the historical development of learning theories from behaviorist through to cognitive models. The chapters also cover memory, motivation, social learning, machine learning, and artificial intelligence. The author's highly entertaining style clarifies concepts, emphasizes practical applications, and presents a thought-provoking, narrator-based commentary. The stage is given to Mrs Gribbin and her swashbuckling cat, who both lighten things up and supply much-needed detail. These two help to explore the importance of technology for simulating human cognitive processes and engage with current models of memory. They investigate developments in, and applications of, brain-based research and plunge into models in motivation theory, to name but a few of the adventures they embark upon in this textbook.

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The Probability Companion for Engineering and Computer Science

90 折

40.

The Probability Companion for Engineering and Computer Science

出版日：2019/11/30 作者：Adam Prügel-Bennett 出版社：Cambridge Univ Pr 裝訂：平裝

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

優惠價： 9 2537

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熱搜：

Machine Learning Applications In Software Engineering

Industrial Applications of Machine Learning

Density Ratio Estimation in Machine Learning

Machine Learning In The Aws Cloud

Software Engineering Research, Management and Applications

Data Management in Machine Learning Systems

Artificial Intelligence and Machine Learning Fundamentals

Machine Learning: The Ultimate Guide to Machine Learning, Neural Networks and Deep Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

Software Languages ― Syntax, Semantics, and Metaprogramming

Machine Learning: A Concise Introduction

The International Conference on Advanced Machine Learning Technologies and Applications (Amlta2018)

Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Data-driven Science and Engineering ― Machine Learning, Dynamical Systems, and Control

Ensemble Classification Methods With Applications In R

Essentials of Software Engineering

Machine Learning and Security ─ Protecting Systems With Data and Algorithms

Handbook of Machine Learning ― Optimization and Decision Making

Big Data And Machine Learning In Quantitative Investment

Deep Learning Illustrated ― A Visual, Interactive Guide to Artificial Intelligence

Machine Learning with Python: A Step-By-Step Guide to Learn and Master Python Machine Learning

Advanced Applications in Manufacturing Engineering

Source Separation and Machine Learning

Solving Partial Differential Equation Applications With Pde2D

Optimization Techniques And Applications With Examples

Deep Learning for Nlp and Speech Recognition

Practical Machine Learning and Image Processing ― For Facial Recognition, Object Detection, and Pattern Recognition Using Python

Multiview Machine Learning

Machine Learning Using R ― With Time Series and Industry-based Use Cases in R

Foundations of Machine Learning

Algorithmic Aspects of Machine Learning

Algorithmic Aspects of Machine Learning

Deep Learning Cookbook ― Practical Rrecipes to Get Started Quickly

Human and Machine Learning ― Visible, Explainable, Trustworthy and Transparent

The Essence of Software Engineering

Advances in Machine Learning and Data Science ― Recent Achievements and Research Directives

Introduction to Machine Learning With R ― Rigorous Mathematical Analysis

Data Intensive Computing Applications for Big Data

Engineering Analysis With Ansys Software

Rock Mechanics and Rock Engineering

Theories of Human Learning ― Mrs Gribbin's Cat

The Probability Companion for Engineering and Computer Science