This is the code repository for Hands-On Natural Language Processing with Pytorch [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
The main goal of this course is to train you to perform complex NLP tasks and build intelligent language applications using Deep Learning with PyTorch. You will build two complete real-world NLP applications throughout the course. The first application is a Sentiment Analyzer that analyzes data to determine whether a review is positive or negative towards a particular movie. You will then create an advanced Neural Translation Machine that is a speech translation engine, using Sequence to Sequence models with the speed and flexibility of PyTorch to translate given text into different languages. By the end of the course, you will have the skills to build your own real-world NLP models using PyTorch's Deep Learning capabilities.
- Processing insightful information from raw data using NLP techniques with PyTorch
- Working with PyTorch to take advantage of its maximum speed and flexibility
- Traditional and modern NLP methods & tools like NLTK, Spacy, Word2Vec & Gensim
- Implementing word embedding model and using it with the Gensim toolkit
- Sequence-to-sequence models (used in translation) that read one sequence & produces another
- Usage of LSTMs using PyTorch for Sentiment Analysis and how its different from RNNs
- Comparing and analysing results using Attention networks to improve your project’s performance
To fully benefit from the coverage included in this course, you will need:
To fully benefit from the coverage included in this course, you will need:
● Python Programming skill
● Some understanding of NLP
● Basic understanding of matrix operations
This course has the following software requirements:
This course has the following software requirements:
● Python 3
● Pip installer
● Jupyter Notebook
This course has been tested on the following system configuration:
● OS: Any modern OS (Windows, Mac, or Linux)
● Processor: An Intel i7 processor
● Memory: 8-16GB of RAM
● Hard Disk Space: 250MB
● Video Card: Nvidia Graphics Card is highly recommended