Machine Learning

Summary#

It took me 1,577 days to complete my undergraduate degree in Computer Science.

Overall, I think the degree was worthwhile and satiated my desire to obtain an understanding of Computers from the bit-level.

I was first introduced to this concept by Distrotube (Derek Taylor’s) “literate config” files. At the time I was not using emacs and thus all the code I was writing was sparingly commented.

Since then, I have entered a world of Machine Learning and Deep Learning, where suddenly in 4 lines, I can sit atop my high-horse and perform sentiment analysis with tensorflow and keras!

from transformers import pipeline
classifier = pipeline('sentiment-analysis')
prediction = classifier("Donald Knuth was the greatest computer scientist.")[0]
print(prediction)

In such an age of abstraction complexity, it becomes paramount to distill what is happening at the last few \((n-k)\) layers.

Knowledge is a paradox. The more one understand, the more one realises the vastness of his ignorance.