Hands-On Natural Language Processing with PyTorch
Build smart language applications using Deep Learning
Created by Jibin Mathew
Explore how to build real-world natural language processing applications using deep learning and PyTorch. You'll create a sentiment analyzer and a neural machine translation engine, gaining hands-on experience with advanced NLP techniques and practical model development.
Packt | Jan 2019 | 144 min
What You Will Learn
You'll start by understanding the core concepts behind each NLP task, then move straight into practical implementation. By working through each project step by step, you'll see how to process text data, train deep learning models, and apply them to real-world language problems using PyTorch.
Key Features
- Build a movie review sentiment analyzer using RNNs and LSTMs in PyTorch
- Develop a neural translation engine with sequence to sequence models and attention
- Master data preprocessing and word embeddings with NLTK, spaCy, and gensim
Target Audience
Designed for developers, researchers, and aspiring AI data scientists with a basic background in machine learning and Python. If you're ready to deepen your skills and build intelligent language applications, you'll find practical guidance and hands-on projects to help you reach your goals.
