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1
Intro
2
Why NLP is Difficult
3
The Turing Test
4
Criticisms
5
Rulebased vs Statistical
6
Encoding Words
7
Word Math
8
Resources
9
What is Dialogflow
10
Creating an Intent
11
Creating a Second Intent
12
Entities
13
Prebuilt Agents
14
Slot Filling
15
Idea Followup
16
Intent Followup
17
Action Parameters
18
Fulfillment
Description:
Dive into the fundamentals of natural language processing (NLP) in this comprehensive tutorial video. Explore key NLP components including entities, relations, concepts, and semantic roles, and discover enterprise applications of this technology. Learn why NLP is challenging, understand the Turing Test and its criticisms, and compare rule-based and statistical approaches. Gain practical skills by building a simple FAQ chatbot using Dialogflow, covering topics such as creating intents, working with entities, utilizing prebuilt agents, and implementing slot filling. Led by Chris Shei, technical evangelist at Jet.com and Data Science Dojo alumnus, this tutorial offers valuable insights into NLP and chatbot development for both beginners and intermediate learners.

Natural Language Processing 101 - Dialogflow Chatbot

Data Science Dojo
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