The files in this repo showcase some of the work I did in an interesting research project whilst at UIC -- the 3 datasets that I used in this set are freely available (but just a bit too large to include in a lightweight Git Repo) and are available from the following links:
-
Stocks Data- https://fmpcloud.io (can extend analysis to date range of your choice)
-
Amazon Reviews Data- https://nijianmo.github.io/amazon/index.html#subsets
-
Crypto Data- https://www.kaggle.com/c/g-research-crypto-forecasting
I also put together a few helper functions that complete the base analysis if you provide the correct kinds of input (listed in file & in notebooks) in the GSFU.py file.
If you have any questions feel free to reach out to me- https://ckgresla.github.io/contact/
Huge thanks to:
-
Professor Kyle Cheek & the Center for Applied Analytics
-
Justifying recommendations using distantly-labeled reviews and fined-grained aspects Jianmo Ni, Jiacheng Li, Julian McAuley Empirical Methods in Natural Language Processing (EMNLP), 2019
-
G-Research for the aggregation of Crypto Data
-
fmpcloud for the free API & historical markets data