Quarter 10 - Week 3

The IIMB Vistas are coming up, and the buildup is palpable. Some of the final years have finally begun to ponder if now's a good time to take part in the fest, considering it's their last time to do so! The first years are enthusiastic, some with starry eyes... the others with a newbie enthusiasm to make their mark. The second years are busy co-ordinating, from the PGSEM side of things... to ensure that we do our bit. Pretty much like a family when you think of it... the grand-people are thinking if they've done enough to leave their mark in the sands of time, the young want to go out there and rule the world, and the stuck-in-the-middles are busy paying all the bills.

Business Data Mining & Decision Models

This course name is still such a mouthful, I have to check the previous blog posts to know what the name really is. This week we move along with more means of analysis, and we cover Artifical Neural Networks and Logistic Regression. The funda from the Neural Networks is pretty simple. Assume you have a black box, and you know that there are some inputs going in one end, and some output coming out the other. You take a sample, look at the values and arrive at what weights are to be associated with them in order to get the result. Then you take the next sample, and by applying a set of simple formulae, you find out how wrong the previous weights were and correct the weights based on the current inputs to get the output. And the cycle goes on and on, till hopefully you have such a confused set of weights that begins to predict what the output should be given a set of input values. The prof covers the funda with a case where he used such a thing, and then we marvel at how accurate something can be, and give a contemptuous smirk at all the previous methods we learnt over the last two weeks. Artificial Intelligence rules!!

The next session when we read about Logistic Regression, we find out about how this uses an exponential function to find out what the effect of the input variables can be. While explaining all of it, the prof decides to show us another case study where he applied this and how it gave all awesome results, and we smirk again at the uselessness of the other methods in this study. Funnily enough, this time the Neural Networks method was pretty bad. So, the question then arises that if all the models have an insanely unpredictable error rate, how do you identify the best one for use on incoming data, when it cant even predict past data as accurately. To which the prof sagely responds - It depends on the input format. If you use continuous variables in these two, and bins in those two, then this method is better else that method is better. That's just convenient if you ask me - Tomato / Tomaahto! A value is a value, how does it being continuous affect the model to be used is beyond me, but I didn't do the PhD or run the painstaking tests and examples, so I'll leave it to the wizened old goats and trust their statements as I've done for the last 2.5 years.

P.S. Yet another difference between the PGP and the PGSEM came forth this week - We seem to have a PGP-er attending the class alongwith us, and the chap is definitely the most inspired by this prof. How would I know? Because while his eyes are focussed on the prof like the latter's a wonder of the world, and the prof's simplest joke or statement is met with a wide grin or a vigorous nod or scribble, some of the PGSEMers are more interested in his reactions than the prof. Analytics must really be their holy grail, if they are dive this deep in a lecture. I'm guessing the prof realized he's losing our attention, because he now cracks fewer jokes. Therefore, to be mesmerized 150% or not to be, that's the difference between the young and the 'experienced'. (Bows to a rumbling applause, and a few delirious fainting acts for the earth-shattering gyaan)

Strategic Thinking and Decision Making

'Tis a game this week, and one where a number of PGSEM team look forward to tearing the guts out of one another to be the top boss! Our prof thought now'd be a good time to let us try out rules of game theory, and so asks us to be ready with a strategy to take on the other teams. And so we prepare over the week and come to class, only to realize that the rest of the class is just as nuts as we are! To put it simply, the game was five round of bidding for business and at the very first round, one of the team lands a shocker by going so deep that the rest of the people go blank for a second. From then on, we ran around trying to figure what the other crazy people might do to get the order, and we went into mutual demolition. The price of the winning tender kept going lower and lower... till finally we look at the numbers and realize exactly why this happens in the real world as well.

We then move into some theory, to understand how people can resolve the prisoner's dilemma. After hearing them, I just wonder why we need to learn strategy when obviously the answers lie in the good ol' religious tomes. Be good, care for others, don't fight, forgive people etc. are the way to go in long term relationships. It's not put as lightly as I just did... there's obviously tons of backing, because hey, it's strategy and its based on inter-entity behaviour. The prof ends with a reminder of the quiz next week, and as usual threatens us enough about reading the soporific chapters early on, if we are to do well.

Not much else on campus, other than a guest lecture on Open Innovation. The preps seem to be in full swing for the Vistas, the students seem concerned about the type of projects to choose, it's a normal week.