ML

Even at the cost of annoying folks around me, I’d dare say that 2020 has actually been a fabulous year for me, personally. I learnt quite a bit about myself, learnt a couple of new skills, learnt what I don’t like, what I don’t want to do, fixed a couple of things about my health and more. I’ll try to chronicle these for the rest of the post. I typically consider my date of birth as the beginning of another year. And for a long time, I wrote up my aspirations for the year ahead. But a couple of years back, I found that I couldn’t keep pace with my aspirations and looking back was a tragic opportunity cost all around me. So I stopped doing this. This year, though, I’ll try and redo the aspirations for the year ahead. But I’ll also try to stay realistic. ...

I recently finished a course on Coursera. Machine Learning from Andrew Ng. Its been on my radar for the longest time and after several false starts, I finally completed mid last month. But along the way I learnt two things: I still relish math like I always did. I understood the concepts pretty well and am able to come up with correct solutions. I am somewhat terrible at coding them up. Now that’s a big surprise to me. I’ve been writing code for quite a long time now. After learning half a dozen programming languages and spending almost a decade writing code, it is a bit of a shock that I find it somewhat difficult to code up the algorithms. And especially in Octave/Matlab. I got thinking. I have built an entire application with all its shenanigans using python. I have been running it on AWS for at least 2 years now and I haven’t so much as contacted their support for anything other than increasing limits. And yet, here I am unable to code up a simple nested for loop to implement a linear regression model. I realised the problem to be, again, two-fold. ...