Natural Language Processing in Python - A Complete Guide

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. If you’re a Python developer or data scientist looking to master NLTK library in Python to make your applications smarter, then this course is perfect for you!

This comprehensive 3-in-1 course is an easy-to-follow guide, full of hands-on examples to learn and master the NLTK library in Python and create your own NLP apps. To begin with, you’ll use functions to implement concordance, similarity, and dispersion plotting, and counting in NLTK to easily mine information from large heaps of textual data. Implement string matching algorithms, statistical language modeling, and normalization techniques. Extract meaning and insights from text data such as vector space models. Finally, use semantic parsing to break down the components of a sentence while creating amazing NLP projects in Python.

Towards the end of this course, you'll learn and master the NLTK library in Python to create your own NLP apps. Explore various NLP tasks while enhancing your Python skills in real-world scenarios.

Contents and Overview

This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Natural Language Processing with Python, covers mastering the NLTK library in Python to create your own NLP apps. You will learn how to tokenize various parts of sentences, and how to analyze them. You will learn about semantic as well as the syntactic analysis of the text. During this course, you will learn how to solve various ambiguities in processing human language. You will also gain experience with NLP using Python and will be introduced to a variety of useful tools in NLTK. Plus, you will have an opportunity to build your first NLP application! By the end of this course, you will have the skills and tools to begin solving problems in the growing field of Latent Semantic Analysis

The second course, Mastering Natural Language Processing with Python, covers exploring various NLP tasks while enhancing your Python skills in real-world scenarios. 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 by 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.

The third course, Next Generation Natural Language Processing with Python, covers practical techniques and methods to analyze your text data. This course empowers you to know how to attack this and other text analysis problems to unlock value for your organization. You’ll start by seeing how NLP can help you extract useful information from large collections of text data, and how you can use the latest Python libraries for NLP. Then we’ll show you how to solve a practical problem using NLP by building a spam SMS detector. You’ll also learn to convert words into numbers that can be analyzed. Moving on, we’ll teach you how to accurately label new documents to get an accuracy score and cluster your data together. Finally, you’ll see more advanced analysis and will model text by using vector space models and semantic parsing to break down the components of a sentence. You’ll also work with neural networks and learn how to write believable text.

By the end of the course, you'll learn Python like a professional to build REST APIs & powerful apps using modern Python!

About the Authors

●        Tyler Edwards is a senior engineer and software developer with over a decade of experience creating analysis tools in the space, defense, and nuclear industries. Tyler is experienced using a variety of programming languages (Python, C++, and more), and his research areas include machine learning, artificial intelligence, engineering analysis, and business analytics. Tyler holds a Master of Science degree in Mechanical Engineering from Ohio University. Looking forward, Tyler hopes to mentor students in applied mathematics, and demonstrate how data collection, analysis, and post-processing can be used to solve difficult problems and improve decision making.

●        Deepti Chopra is an Assistant Professor at Banasthali University. Her primary area of research is computational linguistics, Natural Language Processing, and artificial intelligence. She is also involved in the development of MT engines for English to Indian languages. She has several publications in various journals and conferences and also serves on the program committees of several conferences and journals.

●        Nisheeth Joshi is an associate professor and a researcher at Banasthali University. He has also done a Ph.D. in Natural Language Processing. He is an expert with the TDIL Program, Department of IT, Government of India, the premier organization overseeing language technology funding and research in India. He has several publications to his name in various journals and conferences, and also serves on the program committees and editorial boards of several conferences and journals.

●        Iti Mathur is an Assistant Professor at Banasthali University. Her areas of interest are computational semantics and ontological engineering. Besides this, she is also involved in the development of MT engines for English to Indian languages. She is one of the experts empaneled with TDIL program, Department of Electronics and Information Technology (DeitY), Govt. of India, a premier organization that oversees Language Technology Funding and Research in India. She has several publications in various journals and conferences and also serves on the program committees and editorial boards of several conferences and journals.

Alex Rutherford is a Research Scientist at MIT Media Lab. He has a Ph.D. in Physics and nearly 10 years of experience of using Python for data analysis and modeling gained at the United Nations, Facebook, and elsewhere. He has tackled many problems using data analysis including epidemiology, ethnic violence, vaccine hesitancy, and constitutional change and has built pipelines for social media data, legal documents, and news articles among others. He blogs and tweets regularly on data science and data privacy.