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Machine Learning for Networking

This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN;

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Machine Learning for Networking

This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN;

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The Architecture of Productive Learning Networks

The Architecture of Productive Learning Networks explores the characteristics of productive networked learning situations and, through a;

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The Architecture of Productive Learning Networks

The Architecture of Productive Learning Networks explores the characteristics of productive networked learning situations and, through a;

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Reinforcement Learning for Finance

library. Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN - two;

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Machine Learning for Networking: First International Conference, Mln 2018, Paris, France, November 27-29, 2018, Revised Selected Papers

This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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Advanced Deep Learning with R

Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key;

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Learning in Energy-Efficient Neuromorphic Computing - Algorithm and Architecture Co-Design

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning;

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Strategic Networks

This book explores the creation of 'learning networks' and sheds light on how they function:- real versus virtual forms of interaction;

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MATLAB Deep Learning

Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals;

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Networks for Learning

For Learning is an accessible and thoroughly-researched book, which will be essential reading and a valuable resource for researchers;

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Networks for Learning

For Learning is an accessible and thoroughly-researched book, which will be essential reading and a valuable resource for researchers;

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Deep Learning and Practice with MindSpore

collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes;

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Deep Learning and Practice with MindSpore

collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes;

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Evolutionary Machine Learning Techniques

methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning;

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Evolutionary Machine Learning Techniques

methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning;

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Supervised Learning with Complex-valued Neural Networks

monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The;

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Learning Network Services for Professional Development

creation of distributed Learning Networks and to support the participants with various functions for knowledge exchange, social interaction;

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Optimization, Learning, and Control for Interdependent Complex Networks

This book focuses on a wide range of optimization, learning, and control algorithms for interdependent complex networks and their role;

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Advanced Deep Learning with Python

). Later, you'll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural;

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Handbook on Neural Information Processing

Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple;

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Deep Learning with Python

and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and;

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Deep Learning with Python

and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and;

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Deep Learning for Data Analytics

of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications;

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Hands-on Machine Learning with Python

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It;

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TensorFlow for Deep Learning From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google's revolutionary new software library for deep learning. If;

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