In the past few months, chatbots have made headlines and have become a much-required interface for communication. In this talk, we will discuss three aspects of chatbots:
Level from Northeastern University gives you the skills and real-world experience needed for a career in data analytics. Learn more about the program at www.leveledu.com/seattle.
In this introduction, Instructor Dr. Rutu Mulkar-Mehta and Nick Ducoff, Vice President of New Ventures at Northeastern University, discuss the unique opportunities available through Level.
This tutorial is an introduction to Natural Language Processing using Python, to rapidly build your own NLP module.
We will start with the very basics of NLP - Lemmatization, Stemming, POS tagging, Parsing, Language Models, to the more complex pieces of NLP involving probabilities, statistics and word co-occurrences and finally deep learning approaches to NLP and word vectorization techniques.
As the amount of Unstructured Linguistic Data is increasing each day, it is becoming important to develop tools to analyze this data automatically. In this tutorial I will take you through the basics of linguistic data analytics and then build up to come more complicated pieces of NLP. We will start with basic linguistic techniques - such as Lemmatization, Part of Speech Tagging, Parsing etc, and write some code to implement some these using NLTK. Next, I will talk about how probabilities and statistics are used with Linguistic Data Processing to develop Language Models, and finally we will talk about more complicated techniques such as Deep Learning. In particular we will talk about Word2Vec, its strengths, its weaknesses and how to use it.