3 Things I Wish I Knew When I First Started Machine Learning

As much as we all hope the data, we use is immaculate the reality of it is that many times it is not! Learn standard tools like Pandas and NumPy as they have become tools for me as well as many others on our paths to creating better algorithms. Learning how to deal with "Not a Number" (Nan) is something every person working with data has encountered before. So understanding the effects of different techniques on models whether it be setting the Nan values to extreme values vs just dropping Nan values entirely can drastically change the outcome. At this point, we have all seen the amazing technologies that machine learning and artificial intelligence have brought forward to society, but before jumping into the deep end take the time to understand the fundamentals such as linear regression, K-means clustering, and Naive Bayes.