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    Nov 20 weekly

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    Tuesday, Nov 17
    Today I sepent most of my time on the driving simulator. I learned how to park and turn around properly. I also expiremented with different kinds of cars to get the feel for them.

    Friday, Nov 20
    Today I spent most of my time workign on finishing the machine learning crash course. I learned about different metrics to measure a model. Accurcy = # correct predicitions/ # total predictions. Recall = # positive predicitons/ # correct predictions. Precision = # correct positive predictions/ #positive predictions.

    weekly summary
    this week I learned alot about machine learning and made it through the bulk of the course. I think that what I learned about accuracy, precision, and recall will be very useful as I continue in my project. Accurcy, while it many sound like a good metric, is often misleading. For instance, if you had a model that predicited wheather a person had a very rare diease and if it guessed all negative then its accuracy woudl be pretty good. But it would be an essentially useless model. Precision and Recall are better metrics but are in conflict with each other. when the precision raises the recall falls.