Data Science for Linguists 2023
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LING 1340/2340
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Class Schedule
*Class schedule is subject to revision throughout the semester.
| W | Date | Due (before class @ 9:45am) | Topics Tools |
|
| #To-do/Homework Project |
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| 1 | 1/9 | [slides] Course introduction, setup | ||
| 1/11 | #1 | [slides] Data management and version control | ||
| 1/13 | #2 | [slides] Linguistic datasets | ||
| 2 | 1/18 (W) |
Homework 1: Explore linguistic data | [slides] Processing linguistic data | |
| 1/20 (F) |
#3 | Data processing fundamentals | [slides, JNB] Python's numpy library | |
| 3 | 1/23 | #4 | [slides, JNB] Data frames with pandas | |
| 1/25 | #5 | [slides, JNB] More pandas | ||
| 1/27 | [JNB] Pandas wrap | |||
| 4 | 1/30 | #6 | Statistics | [JNB] Statistics crash course |
| 2/1 | - | [JNB] Stats (ctd), visualization | ||
| 2/3 | Homework 2: Process the ETS corpus (1st half) | [JNB] Stats wrap, visualization | ||
| 5 | 2/6 | Homework 2 (2nd half) | [JNB] HW2 review | |
| 2/8 | #7 | Open access & data publishing, Data mining | [JNB] Twitter mining | |
| 2/10 | #8 (due @9am!!) | Guest speaker: Dr. Lauren Collister | ||
| 6 | 2/13 | Corpora, Annotation | [slides, JNB] Corpora: data formats, HW2 review | |
| 2/15 | - | [slides] Text data files, conversion | ||
| 2/17 | #9 | [slides] Web mining, linguistic annotation | ||
| 7 | 2/20 | #10 | [slides] Annotation continued | |
| 2/22 | - | [slides] Annotation wrap, HW2 revisited | ||
| 2/24 | Machine learning | [JNB1] Regression | ||
| 8 | 2/27 | #11 | [JNB2] Classifiers: count vectors, TF-IDF | |
| 3/1 | - | [JNB2] Continued; Naive Bayes | ||
| 3/3 | - | [JNB3] SVC, categorical data, cross-validation | ||
| No class: Spring break | ||||
| 9 | 3/13 | Homework 3: Machine Learning with ETS data (1st half) | ML (ctd) | [slides] GitHub collaboration, cross-validation, ML comparisons |
| 3/15 | Homework 3 (2nd half) | [JNB2, JNB1] HW 3 review | ||
| 3/17 | #12 | [JNB1, JNB3] HW 3 review | ||
| 10 | 3/20 | - | [JNB3] HW3 wrap: dimensionality reduction, ensemble model | |
| 3/22 | - | Big data at CRC, and Machine learning (ctd), and Advanced NLP | [slides] Shell, command line | |
| 3/24 | [slides] Supercomputing, command line tools | |||
| 11 | 3/27 | #13 | [slides] Running jobs on CRC | |
| 3/29 | #14 | [slides] Big data wrangling, OnDemand on CRC | ||
| 3/31 | - | [slides, JNB1] Computational efficiency, big data wrangling on CRC | ||
| 12 | 4/3 | Homework 4 | [JNB2, JNB3] Advanced NLP, Clustering & topic modeling | |
| 4/5 | #15 | [JNB3, JNB4] Topic modeling, grid search and parallel processing | ||
| 4/7 | - | Speech & multimedia | [slides] Speech data and corpora | |
| 13 | 4/10 | [slides] Speech data tools, forced aligner | ||
| 4/12 | #16 | [slides, JNB] Montreal Forced Aligner, ASR | ||
| 4/14 | #17 | [slides] ELAN demo By Emma, Day 0.5: Sen |
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| 14 | 4/17 | Day 1: Alex, Moldir, Seth | ||
| 4/19 | Day 2: Soobin, Camryn, Mack | |||
| 4/21 | Day 3: Wilson, Ashley, Varun | |||
| 15 | 4/30 (6pm) |
Finals week | ||