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Design of Intelligent Applications using Machine Learning and Deep Learning Techniques

1. This book will attempt to provide a wide range of research and development work under the umbrella of Intelligent Computing. Aim of this;

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Machine Learning for OpenCV 4

concepts for image processing Explore the theory behind machine learning and deep learning algorithm design Discover effective techniques to train;

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Machine Learning and Intelligent Communications

schemes; applications of neural network and deep learning; decentralized learning for wireless communication systems; intelligent antennas design;

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Artificial Intelligence for the Internet of Health Things

applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization;

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Applied Intelligent Decision Making in Machine Learning

of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the;

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

deep learning in clinical applicationsIntroduces several techniques for medical image processing and analysis for CAD systems design;

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Hands-On Deep Learning with R

Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and;

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Mastering Azure Machine Learning

Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using;

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Applied Machine Learning for Smart Data Analysis

, context awareness, analyzing various data sources, machine learning algorithms and intelligent services and applications. Further, it includes;

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Python Machine Learning

, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow;

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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and;

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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and;

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Intelligent Communication and Automation Systems

system design using AI techniques, intelligent signal processing for biomedical applications, intelligent robotic systems, and network security;

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Machine Learning and Deep Learning in Real-Time Applications

have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher;

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Mastering OpenCV 4 with Python

) and Python Apply machine learning and deep learning techniques with TensorFlow and Keras Discover the modern design patterns you should avoid;

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Applications of Artificial Intelligence and Machine Learning

students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor;

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TensorFlow 2.0 Quick Start Guide

will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You;

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Intelligent Learning Systems

recommendation, intelligent interaction support for e-learning, data mining for instructional design, learning and assessment, students' access patterns;

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Deep Learning with TensorFlow 2 and Keras

Features Introduces and then uses TensorFlow 2 and Keras right from the start Teaches key machine and deep learning techniques Understand the;

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Machine Learning in Industry

This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep;

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Python Machine Learning Cookbook

to supervised, unsupervised and reinforcement learning techniques Find easy-to-follow code solutions for tackling common and not-so-common;

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Introducing Machine Learning

Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and;

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Deep Learning for Data Analytics

and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics;

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Learn Computer Vision Using Opencv: With Deep Learning Cnns and Rnns

OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning;

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Deep Learning with Structured Data

Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than;

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Machine Learning for Predictive Analysis

intelligence, intelligent information system development using design science principles, intelligent web mining and knowledge discovery systems.;

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R Deep Learning Cookbook

from text, image and speech * Guide to set-up deep learning models using CPU and GPU Who This Book Is For Data science professionals or;

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