CS 329S | Syllabus
Schedule & syllabus The lecture slides, notes, tutorials, and assignments will be posted online here as the course progresses. Lecture times are 3:15 - 4:45pm PST. All deadlines are at 11:59pm PST. This schedule is subject to change according to the pace of the class. See Past course for the last year's lectures. Date Description Materials Events
CS224U: Natural Language Understanding - Spring 2023
CS224u can be taken entirely online and asynchronously. Our class meetings will be recorded, and the core content will also be delivered via slides, videos, and Python notebooks. MW 3:00–4:20 pm, Gates B1 Discussion Canvas Gradescope Github Staff email: Cloud credits and computing support for student projects generously provided by AWS Educate
Tatsunori Hashimoto | Home
Assistant Professor, Stanford thashim [AT] stanford.edu Bio I am currently an assistant professor at the computer science department in Stanford university. My research uses tools from statistics to make machine learning systems more robust and trustworthy — especially in complex systems such as large language models. The goal of my research is to use robustness and worst-case performance as a len
On the Opportunities and Risks of Foundation Models
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically central yet incomplete character. This report provides a thorough account of the opportunities and risks of foundation models, ranging from their cap
CS224W | Home
Content What is this course about? Complex data can be represented as a graph of relationships between objects. Such networks are a fundamental tool for modeling social, technological, and biological systems. This course focuses on the computational, algorithmic, and modeling challenges specific to the analysis of massive graphs. By means of studying the underlying graph structure and its features
Every single Machine Learning course on the internet, ranked by your reviews
By David Venturi A year and a half ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead. And I could learn it faster, more efficiently, and for a fraction of the cost. I’m almost finished now. I’ve taken m
Stanford University CS231n: Deep Learning for Computer Vision
Course Logistics Lectures: Tuesday/Thursday 12:00-1:20PM Pacific Time at NVIDIA Auditorium. Lecture Videos: Will be posted on Canvas shortly after each lecture. These are unfortunately only accessible to enrolled Stanford students. Office Hours: We will be holding a mix of in-person and Zoom office hours. You can find a full list of times and locations on the calendar. Contact: Announcements and a
CS 229: Machine Learning Final Projects, Autumn 2012
CS 229 Machine Learning Final Projects, Autumn 2012 A Facebook Profile-Based TV Recommender System. Jeff David, Samir Bajaj, Cherif Jazra. [pdf] A Flexible System for Hand Gesture Recognition. Matt Vitelli, Dominic Becker, Laza Upatising. [pdf] A New Rival To Predator And ALIEN. Martin Raison, Botao Hu. [pdf] A Risky Proposal: Designing a Risk Game Playing Agent. Juan Lozano, Dane Bratz. [pdf] A S
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Open Graph Benchmark
Reza Zadeh
http://nlp.stanford.edu/courses/cs224n/2015/reports/24.pdf
Machine Learning | Coursera