Book

• Rolling in changes
• Bumped into Greg C last night. Need to say hi and send a copy after fixing the Deep Bias chapter

SBIRs

• More 3D. Hopefully get everything running. Then start building out the scenario

• Had a good discussion about the experiment logging. I think tables for the folllowing:
  • Program (id, name, brief description, contract start, contract end, status)
  • Project (id, name, brief description, program_id)
  • Code (text) (id, experiment_id, filename, date_stored, code)
  • Figures (blobs) (id, experiment_id, figure name, image)
  • Parameters (id, experiment_id, name, type, string value)
  • Results (same as Parameters)
  • Experiment (id, name, user, brief description, date run, project_id)
• 9:15 standup

GPT Agents

• More DBSCAN. Try to figure out a way to automatically work it out given some statistical measures of the dimensions?
• Got the basics of dbscan working. I was using the wrong id and name

• Added PCA dimension reduction as an option. On the same dataset reduced to 10 dimensions from 100, the clustering still looks good.

• I’m clearly going to need user adjustments for perplexity (TSNE), eps and min_samples (DBSCAN) in the clustering app. Tomorrow.