Course home for
LING 1340/2340

*Class schedule is subject to revision throughout the semester.
| W | Date | Due (before class @ 3:30pm) | Topics Tools |
|
| #To-do/Homework Project |
||||
| 1 | 1/8 | [slides] Course introduction, setup | ||
| 1/10 | #1 | [slides] Data in linguistics | ||
| 2 | 1/15 | Homework 1: Explore linguistic data | [slides] Processing linguistic data | |
| 1/17 | #2 | Data processing fundamentals, statistics | [slides, JNB] Python's numpy library | |
| 3 | 1/22 | #3 | [JNB] Data frames with pandas | |
| 1/24 | #4 | [slides, JNB] More pandas, text processing, stats | ||
| 4 | 1/29 | [JNB] Stats crash course, visualization | ||
| 1/31 | Homework 2: Process the ETS corpus | Putting it all together: HW2 review | ||
| 5 | 2/5 | #5 | [JNB, JNB] To-do 5, HW2 review | |
| 2/7 | Corpus linguistics, annotation | [JNB, slides] HW2 wrap up, corpus concepts, building & processing | ||
| 6 | 2/12 | #6 | [slides] Annotation, data standards & exchange formats | |
| 2/14 | #7 | Open access & data publishing [slides] Guest speaker Lauren Collister | ||
| 7 | 2/19 | #8 | Data mining and machine learning | [JNB, slides] Annotation, data-mining web & social media |
| 2/21 | [JNB] Regression, NB classifier, count vectors, TF-IDF | |||
| 8 | 2/26 | #9 | [JNB] Classifiers continued, categorical data | |
| 2/28 | #10 | [JNB] Dimensionality reduction, cross-validation | ||
| 9 | 3/5 | Homework 3: Data mining & machine learning | [JNB, JNB, JNB] Homework 3 review | |
| 3/7 | #11 | HW3 review, Bash and command line | ||
| No class: Spring break | ||||
| 10 | 3/19 | Big data | [slides] Command line, Bash, grep | |
| 3/21 | #12 | [slides] Supercomputing at CRC, SSH, command line | ||
| 11 | 3/26 | #13 | [slides, Word Embeddings and Clustering] Computational efficiency, machine learning big data, word embeddings | |
| 3/28 | Homework 4: Supercomputing Yelp Data | Homework 4 review | ||
| 12 | 4/2 | #14 | Speech & multimedia | [slides] Speech data, ASR theory |
| 4/4 | #15 | Speech data | ||
| 13 | 4/9 | [slides] More speech data, multimodal data | ||
| 4/11 | #16 | Project presentations | DB, TS, EC | |
| 14 | 4/16 | EB, JS, PS | ||
| 4/18 | KT, MB, CM | |||
| 15 | 4/26 | No class: finals week | ||