Training a Classifier

As I write this post, I have been waiting for the training process to be completed. It's still the first epoch but it feels like it is taking ages.

Forgive me, by the time I uploaded this image, it has reached the 4th epoch. 

The first epoch is yet to be concluded. The accuracy is somehow far from my expectation. Anyway, it's still on the first epoch, so things might be about to change.

At this stage, I am surprised by how much a love-hate relationship is involved in training a classifier. You get excited when your result meets your expected threshold but most of the time, you are left disappointed. 

But still, I cannot find any other things quite interesting to do. I love how data can transform into valuable insight. I love how to spot patterns out of so-called trash and raw data. But really, I am just too lazy to explore further and anticipate more options of workaround to improve the classifier's performance.

Not to mention how intimidated I am to see the progress made by other data scientists around the world, let alone the progress and the advancement of state-of-the-art techniques. Sometimes I feel that I am not good enough in this field. But the big question is: What other fields do you excel at? to which I don't have the answer as well.

So for the first time, I am not after the expertise level whatsoever. I am letting myself drift along the stream of curiosity. Like driftwood as coined by a Scottish band: Travis.

That's it. Thanks for reading this 'sh*tpost'. You have to forgive me for letting all the wild words come out of my fatigued brain. I am just trying to preserve my sanity as much as I can.

I miss Ayah already. See you later, Yah!

London,  8th February 2022