The lecture schedule will be updated as the term progresses.
Make sure to fill out the pre-course survey that is available Piazza.
Make sure you are registered for the course Gradescope and Piazza.
| Date | Topic | Reading | Assignment |
|---|---|---|---|
| Wed, Jan 18, 2023 |
Lecture 1 Course Introduction & Linguistics 101 (working with text) [slides] |
Chapter 2.2 - Chapter 2.6
Chapter 8.1 - 8.1 |
HW00 - Python Warmup
(Due Mon, Jan 23, 2023)
Reading 01 - Text as Data Overview (Due Mon, Jan 23, 2023) |
| Mon, Jan 23, 2023 |
Lecture 2 Language Modeling [slides] |
Chapter 3
|
HW01
(Due Mon, Jan 30, 2023)
|
| Wed, Jan 25, 2023 |
Lecture 3 Document Term Matrix BoW, similarity metrics, tf-idf [slides] |
Chapter 6.3-6.7
|
|
| Mon, Jan 30, 2023 |
Lecture 4 Dimensionality Reduction LECTURE DURING LAB SLOT [slides] |
Chapter 11 of Mining Massive Datasets
|
Reading 02 - TF-IDF & LSA
(Due Mon, Feb 6, 2023)
HW02 - TF-IDF & SVD (Due Wed, Feb 8, 2023) |
| Wed, Feb 1, 2023 |
Lecture 5 Word Representations/Embeddings [slides] |
Chapter 6.8-6.13
|
|
| Fri, Feb 3, 2023 |
Last day to drop a fifth course at Bryn Mawr and Haverford.
|
||
| Mon, Feb 6, 2023 |
Lecture 6 Clustering Topic Modeling I [slides] |
Chapter 15.1: K-Means Revisting (A Course in Machine Learning by Hal Daumé III)
Applications of Topic Models (Boyd-Graber, Hu, Mimno): Chapters 1, 3 Optional: Chapter 2 |
Reading 03 - Topic Modeling (LDA)
(Due Mon, Feb 13, 2023)
HW03 - Topic Modeling (LDA) (Due Wed, Feb 15, 2023) |
| Wed, Feb 8, 2023 |
Lecture 7 Topic Modeling II Dictionary Based Methods [slides] |
Applications of Topic Models (Boyd-Graber, Hu, Mimno): Chapters 9, 10
Jurafsky & Martin: Chapter 25 |
Reading 04 - Dictionary Methods & Applications
(Due Mon, Feb 20, 2023)
|
| Date | Topic | Reading | Assignment |
|---|---|---|---|
| Mon, Feb 13, 2023 |
Lecture 8 Classification Linear & Logistic Regression [slides] |
Chapter 5 |
|
| Wed, Feb 15, 2023 |
Lecture 9 SGD, Feed Forward Neural Networks |
Chapter 7 |
HW04 - Logistic Regression (SGD)
(Due Wed, Mar 1, 2023)
|
| Mon, Feb 20, 2023 |
Lecture 10 Feed Forward Neural Networks Neural Language Models [slides] |
Chapter 7
|
|
| Wed, Feb 22, 2023 |
Lecture 11 Backpropagation Pytorch |
Chapter 7 |
Final Project - Project Ideation
(Due Fri, Mar 3, 2023)
|
| Fri, Feb 24, 2023 |
Last day to declare Cr/NC for full semester courses (5 p.m.).
|
||
| Mon, Feb 27, 2023 |
Lecture 12 Recurrent Neural Networks [slides] |
Chapter 9
|
Reading 05 - Word Embeddings
(Due Mon, Mar 6, 2023)
|
| Wed, Mar 1, 2023 |
Lecture 13 Recurrent Neural Networks |
Chapter 9 Chapters 14 - 16 (Neural Networks for NLP textbook - on Piazza) |
|
| Tue, Mar 7, 2023 |
SPRING BREAK
|
||
| Thu, Mar 9, 2023 |
SPRING BREAK
|
||
| Mon, Mar 13, 2023 |
Lecture 14 LSTM Sentence Representations Probing Attention [slides] |
Chapter 9
Probing Classifiers: Promises, Shortcomings, and Advances (Belinkov 2022) (Optional) |
HW05 - Pytorch
(Due Mon, Mar 20, 2023)
|
| Wed, Mar 15, 2023 |
Lecture 15 Attention Transformers (BERT, GPT) [slides] |
Chapter 10
|
|
| Mon, Mar 20, 2023 |
Lecture 16 Masked Language Modeling Self-Attention, Transformers [slides] |
Chapter 11
|
|
| Wed, Mar 22, 2023 |
Lecture 17 Fine Tuning Masked Language Modeling [slides] |
Chapter 11
|
|
| Mon, Mar 27, 2023 |
Lecture 18 Evaluation Metrics Crowdsource Annotations [slides] |
||
| Wed, Mar 29, 2023 |
Lecture 19 Decoding Evaluating Text Generation [slides] |
| Date | Topic | Reading | Assignment |
|---|---|---|---|
| Mon, Apr 3, 2023 |
Lecture 20 Hypothesis Testing [slides] |
||
| Wed, Apr 5, 2023 |
Lecture 21 Hypothesis Testing II PASSOVER EVE remote lecture [slides] |
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| Mon, Apr 10, 2023 |
Lecture 22 Midterm Review (remote lecture) [slides] |
||
| Wed, Apr 12, 2023 |
Lecture 23 Midterm I |
||
| Mon, Apr 17, 2023 |
Lecture 23 Hypothesis Testing III (Quantifying Variability) [slides] |
||
| Wed, Apr 19, 2023 |
Lecture 24 Hypothesis Testing IV Bootstrap for comparing prediction models Central Limit Theorem [slides] |
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| Mon, Apr 24, 2023 |
Lecture 25 TBD |
||
| Wed, Apr 26, 2023 |
Lecture 26 Project Presentations |