Natural Language Processing (NLP) in Business Applications
Time and Location
Apr 18, 2020 at 9:00am - 3:00pm EDT
Cobb Galleria Center
Agenda
Summary of NLP
1 hour
In this session, we will go through an introduction, learning resources, techniques and major business applications in NLP.
Break 15 min
Unsupervised machine learning for NLP
1.5 hour
This session will be a hands-on python coding tutorial to learn about texting data pre-processing, K-means clustering techniques and TSNE for high dimension data visualization. We will also share some use cases on product categorization based on product description and topic retrieval from review data.
Lunch break 1 hour
Semi-supervised NLP classification
2 hours
In this session, we will go through a real business application with semi-supervised NLP classification. We will share an end to end business project on how to assist new product launch in telecom industry with voice of customer data. There will be a hands on python session on how to use word-2-vec to build keyword dictionary and how to do sentiment analysis with NLTK.
Break 15 minutes
Deep Learning in NLP
2 hours
In this session, we will go through how deep learning LSTM algorithm was applied in a real business case to optimize new product onboarding process to e-commerce website. There will be a hands-on python session on a public data set of news to go through the same LSTM classification methodology.
Jingjing Cannon, Data Scientist at Home Depot.
Bio coming soon..
