30+ Machine Learning Resources
Table of Contents
For almost all machine learning projects, the main steps of the ideal solution remain same. Briefly, we all go over the steps below each and every time: Understand the dataClean up, fix the missing values, extract new features, select the best onesBuild the model, compare it with the other ones, tune hyper parameters, find out what is the right metric to evaluate your modelIterate this process over and over again until you believe you have the best solution:) Iterate this process over and over again until you believe you have the best solution:)
During each step, I had to do some research on the web depending on my business object and jotted down the best resources I ran across. The resources include Online Courses, Kernels from Kaggle, Cheat Sheets and Blog Posts. Below I’ve listed them and categorised by each step (all of the resources are free except the ones that have ‘paid’ in the end):
Source: medium.com
