Abstract: In this session, you will gain a conceptual understanding of Natural Language Processing (NLP) techniques, and learn how to apply them through hands-on projects. You will begin with preprocessing steps necessary for parsing unstructured text data. You will then transform text using representations such as bag-of-words and TF-IDF. You will then perform topic modeling using an LDA model. Next, you will learn how Deep Neural Networks can be applied to NLP tasks, using word embeddings and RNN architectures. Finally, you will apply RNNs to perform sentiment analysis on movie reviews. The projects will be implemented in Python, and libraries like Scikit-Learn, NLTK and Keras, and starter code will be provided through GitHub.
Bio: Luis Serrano is the Content Lead for the Artificial Intelligence Nanodegree Team at Udacity. Previously he was a Machine Learning Engineer at Google for 2 years, working on the video recommendations at YouTube. Before that, he was an academic, and worked as a postdoctoral fellow and instructor in Mathematics at the University of Quebec at Montreal. Luis obtained his PhD in Mathematics at the University of Michigan, and his Bachelors and Masters in Mathematics at the University of Waterloo.
Luis Serrano, PhD
Content Lead for the Artificial Intelligence Nanodegree Team at Udacity