We spent this morning with Jeff providing our weekly update in regards to our projects. Everyone is at that part of their research where they may have hit a wall- there have been a lot of problems and it’s difficult to find exactly how to fix the problems. It’s very helpful to have such a great group of people to bounce ideas off. You can see that a lot of the people in our group had some ideas to help people. The only problem with my project is that so few people know MATLAB, so there weren’t many ideas of how to fix my problem.
Another interesting fact is that 3 other groups are going to be using WEKA in their projects. I had never heard of WEKA- it’s a data mining software. Take a look: http://www.cs.waikato.ac.nz/ml/weka/
We then talked about big data and machine learning, in regards to smartphones and texting. Phones can learn so much from input, and predict words (and grow their dictionary). We worked on using a dictionary and based on a (mistyped) set of letters, the algorithm could predict what the word actually should have been. It’s a pretty neat exercise, and highly useful for learning language. Apple already does this on a large scale with Siri. It’s based upon the “hidden Markhov model.”
Here’s a screenshot of the activity:
And here’s the actual link to the activity: https://www.cs.drexel.edu/~introcs/Fa14/labs/L9-loopsAI/Markov/TheWord2.html (make sure that you import a dictionary!)
We then went over to the DUCA students, and watched them. The were working on Brute-Force cracking a key (they were using small numbers in this scenario, so it is doable.) It was very interesting to see such a range of abilities- some students were comfortable, and some were struggling to understand how exactly the whole thing worked. All of the students, however, were thoroughly engaged in the activity.
I’m now working on trying some more solutions on MATLAB. I’ll post if I have a major breakthrough, but I think I need to rewrite the entire function to make it work.