Content: The lecture by Shuawi Ji was very interesting, everything took a while to sink in, but at the end it all made sense. Machine learning is programming computers to learn by previous data. The learning process can be supervised or unsupervised. Supervised learning are using classifications and clustering. The method of classification was really easy to understand. In constrast, I had a bit of trouble understanding clusters, more specfically where to actually draw the border (choosing a k-value).
Dr. Petitti's Lecture was also very interested and easy to understand. She gave brief introduction to study design, while giving classic examples. Dr. Petitti really did a great job at explaining the difference between observational study and a descriptive study. I really think that the methods introduced in this lectures will be very helpful for my term project. I just have to think how I can apply them.
Posted by P Ortiz
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