Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Stanford University

Stanford CS224U - Natural Language Understanding - Spring 2021

Stanford University via YouTube

Overview

Google, IBM & Meta Certificates – 40% Off
One Coursera Plus subscription covers most Professional Certificates on Coursera.
Unlock All Certificates
This project-oriented graduate course develops systems and algorithms for robust machine understanding of human language. It combines linguistics, natural language processing, and machine learning through topics including representations, contextual models, grounding, inference, retrieval, evaluation, and adversarial analysis.

Syllabus

Introduction and Welcome | Stanford CS224U Natural Language Understanding | Spring 2021
Course Overview | Stanford CS224U Natural Language Understanding | Spring 2021
Homework 1: Word Relatedness | Stanford CS224U Natural Language Understanding | Spring 2021
High-level Goals & Guiding Hypotheses | Stanford CS224U Natural Language Understanding | Spring 2021
Matrix Designs | Stanford CS224U Natural Language Understanding | Spring 2021
Vector Comparison | Stanford CS224U Natural Language Understanding | Spring 2021
Basic Reweighting | Stanford CS224U Natural Language Understanding | Spring 2021
Dimensionality Reduction | Stanford CS224U Natural Language Understanding | Spring 2021
Retrofitting | Stanford CS224U Natural Language Understanding | Spring 2021
Static Representations | Stanford CS224U Natural Language Understanding | Spring 2021
Homework 2: Sentiment Analysis | Stanford CS224U Natural Language Understanding | Spring 2021
Sentiment Analysis | Stanford CS224U Natural Language Understanding | Spring 2021
General Practical Tips | Stanford CS224U Natural Language Understanding | Spring 2021
Stanford Sentiment Treebank | Stanford CS224U Natural Language Understanding | Spring 2021
DynaSent | Stanford CS224U Natural Language Understanding | Spring 2021
sst.py | Stanford CS224U Natural Language Understanding | Spring 2021
Hyperparameter Search | Stanford CS224U Natural Language Understanding | Spring 2021
Feature Representation | Stanford CS224U Natural Language Understanding | Spring 2021
RNN Classifiers | Stanford CS224U Natural Language Understanding | Spring 2021
Contextual Representation Models | Stanford CS224U Natural Language Understanding | Spring 2021
Transformers | Stanford CS224U Natural Language Understanding | Spring 2021
BERT | Stanford CS224U Natural Language Understanding | Spring 2021
RoBERTa | Stanford CS224U Natural Language Understanding | Spring 2021
ELECTRA | Stanford CS224U Natural Language Understanding | Spring 2021
Practical Fine-tuning | Stanford CS224U Natural Language Understanding | Spring 2021
Homework 3: Colors | Stanford CS224U Natural Language Understanding | Spring 2021
Grounded Language Understanding | Stanford CS224U Natural Language Understanding | Spring 2021
Speakers | Stanford CS224U Natural Language Understanding | Spring 2021
Listeners | Stanford CS224U Natural Language Understanding | Spring 2021
Varieties of contextual grounding | Stanford CS224U Natural Language Understanding | Spring 2021
The Rational Speech Acts Model | Stanford CS224U Natural Language Understanding | Spring 2021
Neural RSA | Stanford CS224U Natural Language Understanding | Spring 2021
Natural Language Inference | Stanford CS224U Natural Language Understanding | Spring 2021
SNLI, MultiNLI, and Adversarial NLI | Stanford CS224U Natural Language Understanding | Spring 2021
Adversarial Testing | Stanford CS224U Natural Language Understanding | Spring 2021
Modeling Strategies | Stanford CS224U Natural Language Understanding | Spring 2021
Attention | Stanford CS224U Natural Language Understanding | Spring 2021
NLU and Information Retrieval | Stanford CS224U Natural Language Understanding | Spring 2021
Classical IR | Stanford CS224U Natural Language Understanding | Spring 2021
Neural IR, part 1 | Stanford CS224U Natural Language Understanding | Spring 2021
Neural IR, part 2 | Stanford CS224U Natural Language Understanding | Spring 2021
Neural IR, part 3 | Stanford CS224U Natural Language Understanding | Spring 2021
Relation Extraction | Stanford CS224U Natural Language Understanding | Spring 2021
Data Resources | Stanford CS224U Natural Language Understanding | Spring 2021
Problem Formulation | Stanford CS224U Natural Language Understanding | Spring 2021
Evaluation | Stanford CS224U Natural Language Understanding | Spring 2021
Simple Baselines | Stanford CS224U Natural Language Understanding | Spring 2021
Directions to Explore | Stanford CS224U Natural Language Understanding | Spring 2021
Overview of Analysis Methods in NLP | Stanford CS224U Natural Language Understanding | Spring 2021
Adversarial Testing | Stanford CS224U Natural Language Understanding | Spring 2021
Adversarial Training (and Testing) | Stanford CS224U Natural Language Understanding | Spring 2021
Probing | Stanford CS224U Natural Language Understanding | Spring 2021
Feature Attribution | Stanford CS224U Natural Language Understanding | Spring 2021
Overview of Methods and Metrics | Stanford CS224U Natural Language Understanding | Spring 2021
Classifier Metrics | Stanford CS224U Natural Language Understanding | Spring 2021
Natural Language Generation Metrics | Stanford CS224U Natural Language Understanding | Spring 2021
Data Organization | Stanford CS224U Natural Language Understanding | Spring 2021
Model Evaluation | Stanford CS224U Natural Language Understanding | Spring 2021
Presenting Your Work: Final Papers | Stanford CS224U Natural Language Understanding | Spring 2021
Writing NLP papers | Stanford CS224U Natural Language Understanding | Spring 2021
NLP Conference Submissions | Stanford CS224U Natural Language Understanding | Spring 2021
Giving Talks | Stanford CS224U Natural Language Understanding | Spring 2021
Conclusion | Stanford CS224U Natural Language Understanding | Spring 2021

Taught by

Stanford Online

Reviews

Start your review of Stanford CS224U - Natural Language Understanding - Spring 2021

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.