更新时间：2021-08-13 16:02:28
封面
Title Page
Copyright and Credits
Hands-On Natural Language Processing with Python
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Foreword
Contributors
About the authors
About the reviewer
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Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
Getting Started
Basic concepts and terminologies in NLP
Text corpus or corpora
Paragraph
Sentences
Phrases and words
N-grams
Bag-of-words
Applications of NLP
Analyzing sentiment
Recognizing named entities
Linking entities
Translating text
Natural Language Inference
Semantic Role Labeling
Relation extraction
SQL query generation or semantic parsing
Machine Comprehension
Textual Entailment
Coreference resolution
Searching
Question answering and chatbots
Converting text-to-voice
Converting voice-to-text
Speaker identification
Spoken dialog systems
Other applications
Summary
Text Classification and POS Tagging Using NLTK
Installing NLTK and its modules
Text preprocessing and exploratory analysis
Tokenization
Stemming
Removing stop words
Exploratory analysis of text
POS tagging
What is POS tagging?
Applications of POS tagging
Training a POS tagger
Training a sentiment classifier for movie reviews
Training a bag-of-words classifier
Deep Learning and TensorFlow
Deep learning
Perceptron
Activation functions
Sigmoid
Hyperbolic tangent
Rectified linear unit
Neural network
One-hot encoding
Softmax
Cross-entropy
Training neural networks
Backpropagation
Gradient descent
Stochastic gradient descent
Regularization techniques
Dropout
Batch normalization
L1 and L2 normalization
Convolutional Neural Network
Kernel
Max pooling
Recurrent neural network
Long-Short Term Memory
TensorFlow
General Purpose – Graphics Processing Unit
CUDA
cuDNN
Installation
Hello world!
Adding two numbers
TensorBoard
The Keras library
Semantic Embedding Using Shallow Models
Word vectors
The classical approach
