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Machine Learning for Social Science Symposium Autumn 2023

Published onDec 17, 2023
Machine Learning for Social Science Symposium Autumn 2023
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Symposium Program

Program Design on Canva: [URL]

Using the Alpaca-LoRA method to fine-tune large language models to analyze social media sentiments

by Yiwei Liang

GitHub:

https://github.com/Rising-Stars-by-Sunshine/STATS201_Yiwei_Final_Project/tree/main

Random forest in Classifying Specific Language Impairment (SLI) / Autistic Spectrum Disorder (ASD) / Typically Developing (TD)

by Yuri Park

GitHub:

https://github.com/yuripark518/STATS201_Autumn2023-Week2/tree/main

Discover the current state of energy and the development trend of renewable energy based on machine learning

GitHub:

https://github.com/Rising-Stars-by-Sunshine/Stats201-Yiming-ML-Project/tree/main

Public Perception on Climate Change--Analyzing Twitter Discourse on Climate Change in the Epoch of Extreme Weather

-Ni Zheng

GitHub:

https://github.com/Rising-Stars-by-Sunshine/STATS201-Final-project-Jenny/tree/main

Sentiment Analysis of WallStreetBets: VaderSentiment, roBERTa, distilRoberta

by Albert Li

GitHub:

https://github.com/Rising-Stars-by-Sunshine/Stats_201_AlbertLi/tree/main

Electrifying Change: Analyzing the Impact of Electric Vehicle Sales on CO2 Emissions in the United States through Linear and Polynomial Regression Models

by Polina Konovalova

GitHub:

https://github.com/Rising-Stars-by-Sunshine/STATS201_Polina_Final_Project/tree/main

Public Transit Access for People with Disabilities: Los Angeles, CA: Poisson Regression Analysis

GitHub:

https://github.com/Rising-Stars-by-Sunshine/STATS201_Chloe/tree/main

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