|
Lecture |
|
|
|
|
|
|
|
|
|
|
Nlp And Text Mining ROH |
Enrollment Information (not real time - data refreshed nightly)
|
|
|
|
|
|
|
|
Class #:
|
22454 | |
Enrollment Capacity:
|
83 |
|
Section:
|
ROH |
|
Enrollment Total:
|
80 |
|
Credits:
|
3.00 credits
|
|
Seats Available:
|
3 |
|
Dates:
|
01/30/2023 - 05/12/2023 |
|
Status:
|
OPEN WITH RESERVES |
|
Days, Time:
|
W , 12:00 PM - 2:40 PM |
| Room: |
Alumni 97 |
view map |
| Location: |
North Campus |
|
|
|
|
|
| Reserve Capacities |
|
|
| Description |
Enrollment Capacity |
Enrollment Total |
|
| CSE: Seats Reserved |
41 |
41 |
|
| Eng Sci MS: AI Seats Reserved |
10 |
10 |
|
| Eng Sci MS Data Sci Seats Rsvr |
10 |
7 |
|
|
|
| Enrollment Requirements |
|
|
|
Prerequisites: Prerequisites: CSE 574. CSE 535 preferred but not required. |
|
|
| Course Description |
|
|
| This course will explore various approaches to text, web and social media mining. Since natural language processing (NLP) is the foundation for most text mining solutions, a major focus of the course is on widely used NLP algorithms. This includes topic models, entity tagging, opinion analysis, information extraction, parsing, summarization, machine translation and question answering. We will cover both traditional, feature-based approaches, as well as recent approaches based on neural embeddings. Several applications utilizing text mining will be covered including social media mining and recommender systems (algorithms powering Amazon, Facebook and Twitter). |
|
|
| Instructor(s) |
|
|
| |
Srihari |
look up |
|
|
|
|
| On-line Resources |
|
|
|
|
|
|
| Other Courses Taught By: Srihari |
|
|
|
|
