Resources

• Piazza. Homework-related announcements and majority of the student Q/A with the instructor / TAs may be done through Piazza. We also have a link for anonymous feedback for the course.

• Slack. Students may reach out to communicate with each other and the instructor / TAs via the private Slack channel, #fall23-csci-499-30054, on the USC Viterbi School of Engineering Classes workspace. To be used sparsely and for quick last minute announcements.

• Blackboard For submitting homework, project reports and occasionally quizzes and for viewing grades.

Required Readings

Required readings and supplementary materials will be available on the course website for each class in PDF form. The textbooks we will follow in this class include:

• Jurafsky and Martin. “Speech and Language Processing.” 3rd Ed. This textbook contains chapters on the fundamentals of natural language processing.
• Eisenstein. “Natural Language Processing.” This textbook contains an overview of machine learning approaches for NLP.
• Goldberg. “Neural Network Methods for Natural Language Processing.” This textbook provides a deep learning perspective towards NLP.

Background Readings

Students might optionally read additional background readings assigned in each class.

• Mitchell. “Machine Learning.” Fundamentals of Machine Learning.