This is the code repository for Mastering Natural Language Processing with Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Natural Language Processing is one of the fields of computational linguistics and artificial intelligence that is concerned with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning.This course will give you expertise on how to employ various NLP tasks in Python, giving you an insight into the best practices when designing and building NLP-based applications using Python. It will help you become an expert in no time and assist you in creating your own NLP projects using NLTK. You will sequentially be guided through applying machine learning tools to develop various models. We’ll give you clarity on how to create training data and how to implement major NLP applications such as Named Entity Recognition, Question Answering System, Discourse Analysis, Transliteration, Word Sense disambiguation, Information Retrieval, Text Summarization, and Anaphora Resolution.
- Implement string matching algorithms and normalization techniques
- Implement statistical language modeling techniques
- Develop a search engine and implement POS tagging concepts and statistical modeling concepts involving the n gram approach
- Familiarize yourself with concepts such as the Treebank construct, CFG construction, the CYK Chart Parsing algorithm, and the Earley Chart Parsing algorithm
- Develop an NER-based system and understand and apply the concepts of semantic analysis
- Understand and implement the concepts of Information Retrieval and text summarization
- Develop a Discourse Analysis System and Anaphora Resolution based system
To fully benefit from the coverage included in this course, you will need:
This course is for intermediate level developers in NLP with a reasonable knowledge level and understanding of Python.
This course has the following software requirements:
For all the sections, Python 2.7 or 3.2+ is used.
NLTK 3.0 must be installed either on a 32-bit machine or 64-bit machine.
The operating system that is required is Windows/Mac/Unix.