/100daysofML

my version of 100 days of code by writing code to support my ML learning journey

Primary LanguagePythonMIT LicenseMIT

100daysofML

my version of 100 days of code by writing code to support my ML learning journey

Day 1 - Deciding what to do work on

I took the first day of this challenge to really figure out what I can do in order to best use these 100 days to learn and also build something useful. I landed on this idea, whenever I do ML project or participate in online ML competitions there are some pieces of code especially for exploreation which are super repetitive, I can use the 100 days to write out the code for each of these, test it and publish. on day one I created a small helper function which can be used to prettily pring out how many missing values I have in my data. All commits for a given day are named as such, all code can be found in the src folder.

Day 2 - Perceptron Algorithm

Decided to code up the perceptron algorithm and visualize its working. Still need to work on figuring out the intermediate results lines to be plotted will do it in week 3

Day 3 - Plotting result of the perceptron

finally figured out how to plot the classification boundary while learning the line of best fit with the perceptron algorithm.

100 days of code inspired by Alexander Kallaway