目录 Preface Part I. Basics 1. Getting Started Introduction Other Tools Setting Up Your Environment Prerequisites Starting Apache Spark Checking Out the Code Getting Familiar with Apache Spark Starting Apache Spark with Spark NLP Loading and Viewing Data in Apache Spark Hello World with Spark NLP 2. Natural Language Basics What Is Natural Language? Origins of Language Spoken Language Versus Written Language Linguistics Phonetics and Phonology Morphology Syntax Semantics Sociolinguistics: Dialects, Registers, and Other Varieties Formality Context Pragmatics Roman ]akobson How To Use Pragmatics Writing Systems Origins Alphabets Abiads Abugidas Syllabaries Logographs Encodings ASCII Unicode UTF-8 Exercises: Tokenizing Tokenize English Tokenize Greek Tokenize Geez (Amharic) Resources 3. NLP on Apache Spark Parallelism, Concurrency, Distributing Computation Parallelization Before Apache Hadoop MapReduce and Apache Hadoop Apache Spark Architecture of Apache Spark Physical Architecture Logical Architecture Spark SQL and Spark MLlib Transformers Estimators and Models Evaluators NLP Libraries Functionality Libraries Annotation Libraries NLP in Other Libraries Spark NLP Annotation Library Stages Pretrained Pipelines Finisher Exercises: Build a Topic Model Resources 4. Deep Learning Basics Gradient Descent Backpropagation Convolutional Neural Networks Filters Pooling Recurrent Neural Networks Backpropagation Through Time Elman Nets LSTMs Exercise 1 Exercise 2 Resources Part II. Building Blocks 5. Processing Words 6. Information Retrieval 7. Classification and Regression 8. Sequence Modeling with Keras 9. Information Extraction 10. Topic Modeling 11. Word Embeddings Part III. Applications 12. Sentiment Analysis and Emotion Detection 13. Building Knowledqe Bases 14. Search Engine 15. Chatbot 16. Object Character Recognition Part IV. Building NLP Systems 17. Supporting Multiple Languages 18. Human Labeling 19. Productionizing NLP Applications Glossary Index
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