更新时间：2022-08-25 16:45:32
封面
版权信息
Contributors About the author
About the reviewers
Packt is searching for authors like you
Preface
Section 1: Essentials of PyTorch 1.x for NLP
Chapter 1: Fundamentals of Machine Learning and Deep Learning
Overview of machine learning
Neural networks
NLP for machine learning
Summary
Chapter 2: Getting Started with PyTorch 1.x for NLP
Technical requirements
Installing and using PyTorch 1.x
Enabling PyTorch acceleration using CUDA
Comparing PyTorch to other deep learning frameworks
Building a simple neural network in PyTorch
NLP for PyTorch
Section 2: Fundamentals of Natural Language Processing
In this section……
Chapter 3: NLP and Text Embeddings
Embeddings for NLP
Exploring CBOW
Exploring n-grams
Tokenization
Tagging and chunking for parts of speech
TF-IDF
Chapter 4: Text Preprocessing Stemming and Lemmatization
Text preprocessing
Stemming and lemmatization
Uses of stemming and lemmatization
Section 3: Real-World NLP Applications Using PyTorch 1.x
Chapter 5: Recurrent Neural Networks and Sentiment Analysis
Building RNNs
Introducing LSTMs
Building a sentiment analyzer using LSTMs
Deploying the application on Heroku
Chapter 6: Convolutional Neural Networks for Text Classification
Exploring CNNs
Building a CNN for text classification
Chapter 7: Text Translation Using Sequence-to-Sequence Neural Networks
Theory of sequence-to-sequence models
Building a sequence-to-sequence model for text translation
Next steps
Chapter 8: Building a Chatbot Using Attention-Based Neural Networks
The theory of attention within neural networks
Building a chatbot using sequence-to-sequence neural networks with attention
Chapter 9: The Road Ahead
Exploring state-of-the-art NLP machine learning
Future NLP tasks
Other Books You May Enjoy
Leave a review - let other readers know what you think
