Welcome to the first predict guru idea, this blog is about our experiments to get to know the ideas behind machine learning. Since the time i started learning this fascinating subject, (more scary than fascinating for equation haters like me) i felt like we can apply this technique for many more things other than Fishers IRIS data or the US postal departments ocr data. The following are the things i am planning to try out.
- Cricket player score prediction: Lots of money is involved in cricket betting, imagine the amount of money u can make if u know how much Tendulkar or Sehwag is going to score in a series. I guess given a right model this can be easily predicted, I mean if not the exact number of runs, a range in which each player will score in a series of say 5 matches. Look out for ideas for the model later. This idea can be extended to other games as well.
- This idea is about predicting people. Companies spend a lot of money trying to get the right person, right now interviewing and testing is more of an art which is left to the existing employees who may not be readily available. Why not use machine learning techniques here. One way to do it is to provide a questionnaire to the interviewee as well as some of the ideal employees of an organization. Based on the distance between the expected and the interviewees response, a HR person can quickly discover if a candidate can move forward to the next level.
- Software code review is another area where people use subjective assesments. Again code reviewed by experts can be compared with the new code to evaluate it.
Although some of these look like jobs for expert systems, the idea here is to learn the rules statistically.