Deep Learning for Natural Language Processing [electronic resource] : Solve Your Natural Language Processing Problems with Smart Deep Neural Networks

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자료유형	e-Book
서명/저자사항	Deep Learning for Natural Language Processing [electronic resource]: Solve Your Natural Language Processing Problems with Smart Deep Neural Networks.
개인저자	Reddy Bokka, Karthiek.  Hora, Shubhangi.  Jain, Tanuj.  Wambugu, Monicah.
발행사항	Birmingham: Packt Publishing, Limited, 2019.
형태사항	1 online resource (372 pages).
기타형태 저록	Print version: Reddy Bokka, Karthiek. Deep Learning for Natural Language Processing : Solve Your Natural Language Processing Problems with Smart Deep Neural Networks. Birmingham : Packt Publishing, Limited, 짤2019 9781838550295
ISBN	1838553673 9781838553678
일반주기	Exercise 22: Application of a Simple CNN to a Reuters News Topic for Classification
내용주기	Intro; Preface; Introduction to Natural Language Processing; Introduction; The Basics of Natural Language Processing; Importance of natural language processing; Capabilities of Natural language processing; Applications of Natural Language Processing; Text Preprocessing; Text Preprocessing Techniques; Lowercasing/Uppercasing; Exercise 1: Performing Lowercasing on a Sentence; Noise Removal; Exercise 2: Removing Noise from Words; Text Normalization; Stemming; Exercise 3: Performing Stemming on Words; Lemmatization; Exercise 4: Performing Lemmatization on Words; Tokenization Exercise 5: Tokenizing WordsExercise 6: Tokenizing Sentences; Additional Techniques; Exercise 7: Removing Stop Words; Word Embeddings; The Generation of Word Embeddings; Word2Vec; Functioning of Word2Vec; Exercise 8: Generating Word Embeddings Using Word2Vec; GloVe; Exercise 9: Generating Word Embeddings Using GloVe; Activity 1: Generating Word Embeddings from a Corpus Using Word2Vec.; Summary; Applications of Natural Language Processing; Introduction; POS Tagging; Parts of Speech; POS Tagger; Applications of Parts of Speech Tagging; Types of POS Taggers; Rule-Based POS Taggers Exercise 10: Performing Rule-Based POS TaggingStochastic POS Taggers; Exercise 11: Performing Stochastic POS Tagging; Chunking; Exercise 12: Performing Chunking with NLTK; Exercise 13: Performing Chunking with spaCy; Chinking; Exercise 14: Performing Chinking; Activity 2: Building and Training Your Own POS Tagger; Named Entity Recognition; Named Entities; Named Entity Recognizers; Applications of Named Entity Recognition; Types of Named Entity Recognizers; Rule-Based NERs; Stochastic NERs; Exercise 15: Perform Named Entity Recognition with NLTK Exercise 16: Performing Named Entity Recognition with spaCyActivity 3: Performing NER on a Tagged Corpus; Summary; Introduction to Neural Networks; Introduction; Introduction to Deep Learning; Comparing Machine Learning and Deep Learning; Neural Networks; Neural Network Architecture; The Layers; Nodes; The Edges; Biases; Activation Functions; Training a Neural Network; Calculating Weights; The Loss Function; The Gradient Descent Algorithm; Backpropagation; Designing a Neural Network and Its Applications; Supervised neural networks; Unsupervised neural networks Exercise 17: Creating a neural networkFundamentals of Deploying a Model as a Service; Activity 4: Sentiment Analysis of Reviews; Summary; Foundations of Convolutional Neural Network; Introduction; Exercise 18: Finding Out How Computers See Images; Understanding the Architecture of a CNN; Feature Extraction; Convolution; The ReLU Activation Function; Exercise 19: Visualizing ReLU; Pooling; Dropout; Classification in Convolutional Neural Network; Exercise 20: Creating a Simple CNN Architecture; Training a CNN; Exercise 21: Training a CNN; Applying CNNs to Text
요약	Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.
일반주제명	Natural language processing (Computer science) Neural networks (Computer science) Machine learning. Machine learning. Natural language processing (Computer science) Neural networks (Computer science) Deep learning Natu?rliche Sprache
분류기호(DDC)	006.35
언어	영어
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