Hello learners!
Nearly year ago, My friend Amit and I (Siddharth) were introduced to this amazing field of Machine Learning.
We were 2nd year computer engineering undergrads with good amount of experience in Python. So it was very normal
for us to expect coding first approach of ML and DL. There were lots of good resources available for coding first
ML approaches. We started learning same and after significant amount of time, we found out that things will not
make sense to us at application level if we don't understand theory and math behind it.
After facing issues, we have started creating our own learning material which helps learners to directly
start learning rather than going around internet in search of good resources.
This guide is mainly made of following parts:
→ Theory of Method/Algorithm
→ Math behind Algorithms (No high level methods, just for understanding)
→ Code for implementation
Other than that, We will also be explaining most important math part in modules made entirely for that. It will be easy to navigate style website with no coding interface included. Code snippets will be highlighted in different style to keep things easy to read.