Document the file size, MD5/SHA-256 hashes, and the tools used to extract it (e.g., 7-Zip, FTK Imager).
Use visualizations like histograms or heatmaps to show where the "bias" exists in the data. Bias.7z
(e.g., a specific university course, a CTF platform like HackTheBox, or a workplace task)? Document the file size, MD5/SHA-256 hashes, and the
Suggest ways to "de-bias" the model, such as re-weighting the data or using a GMM estimator for improved estimation . Option 3: Financial Trade Classification Document the file size
Explain how you tested for bias (e.g., checking for disproportionate outcomes across demographic groups).
(e.g., .exe, .pcap, .csv, .txt)?
Discuss how classification errors lead to downward bias in effective spreads.