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  • Foundations of Statistical Algorithms

    With References to R Packages

    Collections series Chapman & Hall/CRC Computer Science & Data Analysis
    A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundations of Statistical Algorithms: With References to R Packages reviews the historical development of basic algorithms to illuminate the evolution of today's more powerful statistical algorithms. It emphasizes recurring themes in all statistical ... En savoir plus

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  • Hyperparameter Tuning for Machine and Deep Learning with R

    A Practical Guide

    Collections series Computer Science (R0)
    This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods ... En savoir plus

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  • Python Deep Learning

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    Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.Key Features\[\*\] Explore and create intelligent systems using cutting-edge deep learning techniques\[\*\] Implement deep learning algorithms and work with revolutionary libraries in Python\[\*\] Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and ... En savoir plus

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  • Hands-On Mathematics for Deep Learning

    Build a solid mathematical foundation for training efficient deep neural networks

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  • Automated Machine Learning

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    Collections series The Springer Series on Challenges in Machine Learning
    This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML ... En savoir plus

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    Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization. Since its introduction, inductive modelling has been developed to support complex systems in prediction, clusterization, system identification, as well as data mining and knowledge extraction technologies in social science, science, engineering, and medicine.This is the first ... En savoir plus

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    Restricted Boltzmann Machines and Supervised Feedforward Networks

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