Demystifying Natural Language Processing across several industry verticals
summary
Lists concrete industry wins—e‑commerce search and review sentiment, finance signals from social posts, real estate auto‑fill that boosts listing value 1–6%, social media topic and trend extraction—then shows what was actually built: a toy lexicon sentiment classifier and an NLTK+WordNet rule‑based chatbot that falls back on canned replies. Recommends tools such as VADER, TextBlob, spaCy and hosted NLU (Dialogflow) and compares them to open source like Rasa and ChatterBot, explaining practical tradeoffs between lexicons, ML classifiers, and full intent/entity pipelines.
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chapters (14)
- 0:00Introduction
- 1:14What is NLP
- 4:23NLP industry applications
- 5:25NLP in e-commerce
- 9:34NLP in finance
- 13:05NLP in real estate
- 18:43NLP in social media
- 23:45NLP in marketing
- 30:04NLP in email
- 31:07Sentiment analysis tools
- 38:51Chatbot architecture
- 44:26Building AI chatbots
- 51:00Chatbot solutions
- 54:30Q&A
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