Current stage: Entry ML concepts Learned for: 6h but productivity-wise, 3 Satisfied? Nah

Continued reading the FastAI book & watching the course; learned more top-level concepts and wrote code but disliked all the simplified wrappers.

Things I found interesting:

  • Feature Engineering: a process of using domain knowledge to extract and create features (input variables) from raw data that make machine learning algorithms work more effectively.

  • Pattern Recognition: A pretrained model has learned patterns and relationships from a wide array of datasets. For instance, it might have learned that in healthcare data, the ratio of two lab values (like cholesterol level to age) often provides more predictive power than those two values separately.

Things I’ve done well today:

  • Finished a 24h fast (yesterday til today)
  • Finished gym (back and shoulders)
  • Rested a ton and napped in the afternoon
  • Technically learned for 6 hours, but so many distractions everywhere that productivity was low