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Now showing items 81-100 of 411

Reverse hypothesis machine learning : a practitioner's perspectives

Kulkarni, Parag (Springer, 2017)

This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. The book is useful as a reference book for machine learning researchers and professionals as well ...
Scala machine learning projects : build real-world machine learning and deep learning projects with Scala

Karim, Rezaul (Packt Publishing, 2018)

Scala is one of the widely used programming language in the world when it comes to handle large amount of data. With the rise of machine learning, data scientists and machine learning experts do prefer scala as a language ...
Machine learning using R

Ramasubramanian, Karthik; Singh, Abhishek (Apress, 2017)
Introduction to machine learning with applications in information security

Stamp, Mark (CRC Press, 2018)
Machine learning : a constraint-based approach

Gori, Marco (Elsevier : MK, Morgan Kaufmann Publishers, 2018)
Lie group machine learning

Fanzhang, Li; Li, Zhang; Zhao, Zhang (De Gruyter, 2019)
Machine learning for model order reduction

Salah Mohamed, Khaled (Springer, 2018)

This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior. The author describes ...
Machine learning for ecology and sustainable natural resource management

Humphries, Grant R. W. ed.; Huettmann, Falk ed.; Magness, Dawn R. ed. (Springer, 2018)

Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species ...
Machine learning using R: with time series and industry-based use cases in R. 2nd ed.

Ramasubramanian, Karthik; Singh, Abhishek (Apress, 2019)

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 it to build a ML model ...
Building intelligent systems : a guide to machine learning engineering

Hulten, Geoff (Apress, 2018)

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to ...
Visual knowledge discovery and machine learning

Kovalerchuk, Boris (Springer, 2018)

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization ...
Feature engineering for machine learning : principles and techniques for data scientists. 1a. ed.

Casari, Amanda; Zheng, Alice (O’Reilly, 2018)

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you'll learn techniques for extracting and transforming features-the numeric ...
Algorithmic aspects of machine learning

Moitra, Ankur (Cambridge University Press, 2018)

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 ...
Machine learning : topics and techniques

Knox, Steven W. (John Wiley & Sons, 2018)
Machine learning in sports identifying potential archers

Muazu Musa, Rabiu; Taha, Zahari; Abdul Majeed, Anwar P. P.; Razali Abdullah, Mohamad (Springer, 2019)
Granular computing based machine learning : a big data processing approach

Liu, Han; Cocea, Mihaela (Springer, 2018)
Kinesthetic perception : a machine learning approach

Chaudhuri, Subhasis; Bhardwaj, Amit (Springer, 2018)

This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones ...
Machine learning paradigms: theory and application

Ella Hassanien, Aboul ed. (Springer Nature Switzerland AG, 2019)
Machine learning paradigms: advances in data analytics

Tsihrintzis, George A. ed.; Sotiropoulos, Dionisios N. ed.; Jain, Lakhmi C. ed. (Springer International Publishing Springer Nature, 2019)
Machine learning techniques for online social networks

Özyer, Tansel; Alhajj, Reda (Springer, 2018)

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