Trimester 2 unit 3 machine learning

 A personal opinion is that if they had stacked up eng AI sol after ML unit I would have gotten enough time to brush up on all related concepts and wouldn't have lapsed on that unit in trime. 1 but yeah clearly hard luck.

Hopping in on a 2 month endeavour today as of now, coz deadlines are pretty tight..

Comparatively math is easy for me to score, and yeah I loved ML in 1st year but it took an entire 7 months to wrap up ML in 1st year which is gonna be done here in hardly 1 n half months.. gotta keep the momentum going too..let's see 🤞🙏 

18/8/24:

I have resubmission of three more projects so yes that extended deadline tab would now look like ;

But thats not even why Im noting this down here today.. well well well, one of those projects was to replicate a worked out case study which used regressor algorithms like LR, SVR, RFR, DTR and even NN. This lengthy case study had to be learnt to even understand what all were used as in hyper parameter tuning and based on this replication a new ML model which is different from all the above or even same but a different approach atleast., obviously with improved performance has to be devised..

Oh my goodness..I just implemented a stacked TASEFS basing SVR, RFR and DTR topped with a meta layer of LR for my model design..and finally that prediction has been perfected.. feels like on top of the world.. after an entire swamped week and that too totally preoccupied with regressor algorithms and case study deets on top of loaded workdays and an entire weekend stuck on attempts to include an NN in the base layer , back to back errors, to and fro corrections, that last minute decision to drop NN and..and add RFR to the base layer.. TASEFS..perfecto..!! Just sighing...relieved..

But thank you God 🙏 please remain being on my side..plz plz plz.. 

31/8/24:

Marking this unit as completed. Just thank you God 🙏🙏🙏