The aim of this post is to explore how to build an understanding of a complex project and contribute to the project by fixing open issues or suggesting future work. This process can be involved and requires consious efforts to stay on track and make measured progress. This is my attempt to chalk out a guide that can help new Open Source contributors to not get lost in the project nitty-gritties and make meaningful contributions while feeling confident about their understanding of the underlying concepts.

I am using the following project to demonstrate the process: neurite

Why Neurite?

It is a toolbox for medical image analysis in tensorflow/keras for now.

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Step 1: Read the paper(s) introducing the project and understand the building blocks thoroughly. This repo features two papers: Unsupervised Data Imputation via Variational Inference of Deep Subspaces Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation —— It is very easy to spend hours, if not days trying to understand every line of a research paper, especially if you are relatively new to the field. Here is a popular aproach for effectively get the most out of a paper

Pass1: Aim of this pass is to read the title, abstract, and conclusion.
Should be able to understand what is the objective of this project and pin-point areas that you should be familiar with to understand this paper.