CSCI 373 Resources

Handouts

• Feb. 14: Introduction to GitHub
• Feb. 23: Confidence Intervals Handout

Readings for April 12: Real-World Machine Learning Tasks

• Bult, L. February 21, 2024. "Can AI help us predict extreme weather". Vox. URL: https://www.vox.com/videos/2024/2/21/24079271/ai-predict-extreme-weather-forecast
• Bassett, A. November 14, 2023. "Is AI the answer to sustainable farming?". The Verge. URL: https://www.theverge.com/2023/11/14/23950666/ai-sustainable-farming-machine-learning-agriculture
• Veltman, C. November 3, 2023. "New tools help artists fight AI by directly disrupting the systems". NPR URL: https://www.npr.org/2023/11/03/1210208164/new-tools-help-artists-fight-ai-by-directly-disrupting-the-systems
• Jain, M. October 28, 2023. "The urgent call for innovation and investment in maternal health". Tech Crunch. URL: https://techcrunch.com/2023/10/28/the-urgent-call-for-innovation-and-investment-in-maternal-health/
• Discussion Prompts
• Reflection Assignment (Due 4/22)

Readings for April 29: Biases and Machine Learning

• Castro, Daniel. September 10, 2014. "The Rise of Data Poverty in America". URL: http://www2.datainnovation.org/2014-data-poverty.pdf
• Dzieza, J. June 20, 2023. "AI is a lot of work". New York Magazine. URL: https://nymag.com/intelligencer/article/ai-artificial-intelligence-humans-technology-business-factory.html
• Levi, R. & Gorenstein, D. June 6, 2023. "AI in medicine needs to be carefully deployed to counter bias - and not entrench it". NPR. URL: https://www.npr.org/sections/health-shots/2023/06/06/1180314219/artificial-intelligence-racial-bias-health-care
• Zewe, Adam. February 21, 2022. "Can machine-learning models ovecome biased datasets?". MIT News. URL: https://news.mit.edu/2022/machine-learning-biased-data-0221
• Discussion Prompts
• Reflection Assignment (Due 5/6)

Recommended Textbooks

• Hastie, Trevor, Tibshirani, Robert, and Friedman, Jerome. The Elements of Statistical Learning. Springer-Verlang, 2009. Website: http://web.stanford.edu/~hastie/ElemStatLearn/
• Mitchell, Tom M. Machine Learning. WCB/McGraw-Hill, Boston, MA, 1997. Website: http://www.cs.cmu.edu/afs/cs.cmu.edu/user/mitchell/ftp/mlbook.html
• James, Gareth, Witten, Daniela, Hastie, Trevor, and Tibshirani, Robert. An Introduction to Statistical Learning (with Applications in R). Springer-Verlang, 2013. Website: https://www.statlearning.com
• Goodfellow, Ian, Bengio, Yoshua, and Courville, Aaron. Deep Learning. MIT Press, Cambridge, MA, 2016. Website: http://www.deeplearningbook.org/