Machine Learning

Content:  I am always glad to hear a lecture that starts to connect ideas together for me.  Like Ashutosh pointed out, this lecture linked to Dr. Shortliffe's lecture on decision making.  He used an example of a decision tree, which gave us another example to build upon when learning about classification algorithms.  This was a new topic for me, so any connections I could make were a bonus.  Mr. Ji's lecture was a great introduction into machine learning and I learned a lot, from the difference between supervised and unsupervised, between classification and clustering and many applications of machine learning.  
The only area that I was a little fuzzy on was that of support vector machines,  I know that he was trying to leave the math out, but it might have been easier to see how they choose a boundary if after the margins were defined an example with real numbers was done. 

Posted by Laura Wojtulewicz