DAT 562, DAT 8562
Text Mining
Text mining extracts valuable insights and actionable information from vast amounts of unstructured textual data. It is a rapidlyevolving field at the intersection of natural language processing and machine learning, and is applied in various domains includinghealthcare, social media analysis, financial prediction and beyond. This undergraduate course covers a wide range of text miningapproaches, from traditional statistical methods to cutting-edge techniques. Students will gain both in-depth knowledge offundamental concepts and hands-on experience in practical applications. Topics of the course include text representation learning,text classification, named entity recognition, relation extraction, taxonomy and knowledge graph construction, and retrieval-augmented generation. Through programming assignments and a semester-long project, students will develop hands-on textmining skills necessary for real-world scenarios. Prerequisite: CSE 417T
Instructors
Reviews
I would advise against selecting this professor, as she tends to solely focus on presenting her own viewpoints during class without providing precise explanations or responses to her students. It is advisable to keep your expectations low for her class. Her course evaluations tend to be irrational and unfair, resulting in unjust scores.
5/15/2023
Her teaching approach seems to primarily involve reading from PowerPoint slides, which lacks logical explanations. There appears to be an issue with unfair grading in the course, and it's disappointing that feedback is unavailable. Hiring such an ineffective professor for a mandatory class has potentially impacted Olin's ranking negatively.
5/15/2023
You can't learn anything in her class, everything has to be done by self-study, the video before the class is just narrating the concept, everything has to be done by yourself, I'm really not sure what the purpose of choosing this class is.
4/17/2022