Building a text classifier - or more appropriately, trying to!

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This exercise took a really long time. I was starting to get bored of running small examples and wanted to really get my hands dirty. I think this semester has helped me understand my inherent impatient and curious nature. One of the things that I learnt about myself through the course of these modules is that I am extremely impatient when it comes to learning.  I want to learn everything fast. I keep jumping topics, skipping videos. In a classroom structure, I can definitely see that I am tied by the speed of the course decided by the professor(some skilled and trained at designing a curriculum). But when left on my own, I keep jumping around and going down rabbit holes. It may seem productive and fast progress at first but it definitely leaves gaps in my understanding.

I did something similar this week. I decided I have read enough blogs and tutorials that I can build a classifier already. I was confident that in my previous module I did work with classifiers, I will be proficient enough to build one using NLTK. I followed some blogs but I kept getting errors. After removing those errors, I got more errors, in the end, I had to go back to datacamp videos, and the NLP book, to fill the gaps in my learning.

So this week was more of watching videos, and practising on datacamp, so that I can figure out how is that classifier working. I think weeks of stuck in stuck in frustration is a rite of passage. If you are not stuck, maybe you not doing something right!

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