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ReRAM-based Machine Learning

using IMC accelerators, present ReRAM-based IMC architectures that can perform computations of ML and data-intensive applications, as well as;

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Algorithms in Machine Learning Paradigms

applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning;

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Algorithms in Machine Learning Paradigms

applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning;

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Quantum Machine Learning with Python

(Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, along;

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Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel;

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Distributed Machine Learning and Gradient Optimization

This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the;

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Machine Learning with Scala Quick Start Guide

covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression;

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Intelligent 802.11 Intrusion Detection

Recent research has shown that machine learning based Intrusion Detection Systems (IDSs) can be used to detect link layer attacks in 802.11;

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Learning scikit-learn

learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous;

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Beginning Machine Learning in iOS

. Many applications on iPhone use machine learning: Siri to serve voice-based requests, the Photos app for facial recognition, and Facebook to;

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Introduction to Machine Learning with R

Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory;

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Machine Learning based Natural Scene Recognition for Mobile Robot Localization i

This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene;

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Knowledge Engineering, Machine Learning and Lattice Computing with Applications

This book constitutes the refereed proceedings of the 16th International Conference on Knowledge-Based and Intelligent Information and;

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Building Machine Learning Systems With Python

-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into;

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Artificial Intelligence, Machine Learning, and Deep Learning

learning architectures such as CNNs, RNNs,LSTMs, and auto encoders. Keras-based code samples are included to supplementthe theoretical discussion;

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Statistics and Machine Learning Methods for EHR Data

The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning;

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Machine Learning for Vision-Based Motion Analysis: Theory and Techniques

to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights;

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Applied Recommender Systems with Python

essential part of every internet-based business today. You'll start by learning basic concepts of recommender systems, with an overview;

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Applied Recommender Systems with Python

essential part of every internet-based business today. You'll start by learning basic concepts of recommender systems, with an overview;

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Mathematics and Programming for Machine Learning with R

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R;

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Mathematics and Programming for Machine Learning with R

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R;

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Source Separation and Machine Learning

deep learning Presents a number of case studies of model-based BSS (categorizing them into four modern models - ICA, NMF, NTF and DNN;

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Machine Learning for Cyber Physical Systems

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers;

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Machine Learning for Cyber Physical Systems

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers;

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Knowledge Acquisition and Machine Learning

For graduate-/research- level students and professors, this book integrates machine learning with knowledge acquisition to overcome the;

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Machine Learning for iOS Developers

) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine;

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Machine Learning and Systems Engineering

A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October;

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