Introduction to NLP - Chapter 8 - Business Data Science Matt Taddy
Using text as insights for business decisions.
00:00 Topics we will cover - index page
01:31 Why use text as Data to solve business problems?
08:18 Spam detection architecture
09:20 Steps to use text as Data
12:04 Tokenization
14:17 Stemming and Stop words removal
15:25 Word Embeddings
19:16 Email as Text - apply logistic regression
20:41 Wordle - word cloud
23:03 Topic models - Algo-22 - PCA for big and sparse data (predict factors)
29:00 MNIR - Multinomial inverse regression (predict ratings/sentiment)
30:47 Collaborative Filtering vs Content Filtering