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The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. “Big data,” “data science,” and “machine learning” have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on a journey through th
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Schedule and Syllabus Unless otherwise specified the course lectures and meeting times are: Wednesday, Friday 3:30-4:20 Location: Gates B12 This syllabus is subject to change according to the pace of the class. Please post on Piazza or email the course staff if you have any question.
To realize the dreams and impact of AI requires autonomous systems that learn to make good decisions. Reinforcement learning is one powerful paradigm for doing so, and it is relevant to an enormous range of tasks, including robotics, game playing, consumer modeling and healthcare. This class will provide a solid introduction to the field of reinforcement learning and students will learn about the
Logistics Lectures: are on Tuesday/Thursday 4:30 PM - 5:50 PM Pacific Time in NVIDIA Auditorium. The lectures will also be livestreamed on Canvas via Panopto. Lecture videos for enrolled students: are posted on Canvas (requires login) shortly after each lecture ends. Unfortunately, it is not possible to make these videos viewable by non-enrolled students. Publicly available lecture videos and vers
There were two options for the course project. Students either chose their own topic ("Custom Project"), or took part in a competition to build Question Answering models for the SQuAD challenge ("Default Project"). You can see the in-class SQuAD challenge leaderboard here. The previous year's reports from CS224n 2017 are available here. Prize Winners Congratulations to our prize winners for having
No class on Friday, Feb 2. See syllabus. For the last year's website, visit here TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google. It has many pre-built functions to ease the task of building different neural networks. TensorFlow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a sin
Mon/Wed 11:00-12:15 at 200-305 A major database system implementation project realizes the principles and techniques covered in earlier courses. Students independently build a complete database management system, from file structures through query processing, with a personally designed feature or extension. Lectures on project details and advanced techniques in database system implementation, focu
by Theodore Roszak Copyright 2000 by Theodore Roszak. All rights reserved. The Times They Keep A-Changin' When this essay was first written for the Alvin Fine Memorial Lecture at San Francisco State University in April 1985, I was not fully aware of how much the times had already changed since I wrote The Making of a Counter Culture in 1969. But I soon learned. A few weeks before the lecture, a st
Schedule and Syllabus Unless otherwise specified the course lectures and meeting times are: Tuesday, Thursday 4:30-5:50 Location: NVIDIA Auditorium
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The Arithmetic of Active Management William F. Sharpe Reprinted with permission from The Financial Analysts' Journal Vol. 47, No. 1, January/February 1991. pp. 7-9 Copyright, 1991, Association for Investment Management and Research Charlottesville, VA "Today's fad is index funds that track the Standard and Poor's 500. True, the average soundly beat most stock funds over the past decade. But is thi
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My web page is HERE
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CME 193: Introduction to Scientific Python Course description: This short course runs for the first three weeks of the quarter and is offered each quarter during the academic year. It is recommended for students who want to use Python in math, science, or engineering courses and for students who want to learn the basics of Python programming. The goal of the short course is to familiarize students
Systems Optimization Laboratory Stanford University Dept of Management Science and Engineering (MS&E) Huang Engineering Center Stanford, CA 94305-4121 USA The following software packages are provided by SOL under the terms of The MIT License (MIT). The software may alternatively be used under the terms of a BSD License (BSDlicense.txt). SYMMLQ: Fortran, MATLAB, and Python software for sparse symm
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Speech and Language Processing (3rd ed. draft) Dan Jurafsky and James H. Martin Here's our Feb 3, 2024 release! We also expect to release Chapter 12 soon in an updated release. Individual chapters and updated slides are below; here is a single pdf of all the chapters in the Feb 3, 2024 release! Feel free to use the draft chapters and slides in your classes, the resulting feedback we get from you m
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