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Deep Learning Based Approaches for Sentiment Analysis

This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has;

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Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks

This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments;

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Emerging Technologies for Healthcare - Internet of Things and Deep Learning Models

sentiment analysis are also discussed with sufficient data and its dimensions. This book not only covers theoretical approaches and algorithms;

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Sentimental Analysis and Deep Learning

discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment;

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Multimodal Sentiment Analysis

extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment;

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Natural Language Processing Recipes

preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language;

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Python Machine Learning

deep learning Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more Build and train;

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R Deep Learning Projects

-world projects related to text generation, sentiment analysis, fraud detection, and more Get to grips with R's impressive range of Deep Learning;

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Text Analytics with Python

sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move;

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Text Analytics with Python

sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move;

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Deep Learning for Medical Image Analysis

>Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad;

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Domain Adaptation in Computer Vision with Deep Learning

state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based;

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Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based;

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Natural Language Processing Recipes

, text summarization, sentiment analysis, information retrieval, and many more applications of NLP. The book begins with text data collection;

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Deep Learning for Data Analytics

, enterprise data science, predictive analysis, optimization for Deep Learning, and feature selection using Deep Learning;

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Sentiment Analysis

Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem;

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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural;

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Affective Computing and Sentiment Analysis

and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being;

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Spectral Geometry of Shapes

analysisGives insights for developing spectral geometry-based approaches for 3D shape analysis and deep learning of shape geometry

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Hands-On Natural Language Processing with PyTorch 1.x

-based neural networks Who this book is forThis PyTorch book is for NLP developers, machine learning and deep learning developers, and anyone;

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Developing Enterprise Chatbots: Learning Linguistic Structures

reasoning approaches with high-performance statistical and deep learning technologies. Today, there are two popular paradigms for chatbot;

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Computer Analysis of Images and Patterns

and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Computer Vision for UAV, DL-UAV 2019;

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Visual Saliency

object detection. For low-level tasks, the authors focus on pixel-level image processing approaches based on efficient distance;

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Advanced Machine Learning Approaches in Cancer Prognosis

learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted;

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Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process;

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Statistics and Machine Learning Methods for EHR Data

approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting;

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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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