This repository is a boilerplate template for Flatiron School captstone projects. The idea here is that you can take this repository and use it as jumping off point to structure your project so you don't have to re-invent the wheel in terms of the organization of the project. If you don't like how this repo is organised, you don't have to stick to it, feel free to change it. That said, this format here is a tried and tested format that should work for you!
The way to use this template is to just copy and paste the file structure (don't fork it, you don't want to be just manipulating a template!) to your new initialized repo and fill in things where they should go.
We also suggest if you need direction to check out the Project Checklist markdown file that is found in this repository as well as the Capstone Questions document for help building and assessing this project.
Both this boiler plate and the checklist were built simultaneously, so feel free to use them in tandem.
Eventually you will delete everything above this line. This is just here to introduce the boilerplate. We also suggest deleting any other indentations like this. There are more there to get you thinking about the 'point' of the section.
One sentence summary goes here saying what you did. A second sentence goes here says why it matters. A last sentence links to any productionized web dashboard here.
You can also link to
We suggest that people follow a "Facebook Page" approach to writing up their README. This means that the most important information is at the top (your name, point of project, contact info) and then as you go down the document you get less and less relevant information. Remember that you are NOT writing a detective story and need to find a way to present as much information as quickly as possible to the person that will be looking at this for 45 seconds tops. Of course others might look for longer, but the UX/UI of your REAMDE should be done with the 'github skimmer' in mind.
Start with one or two sentences here that contextualises what your project matters here. These two sentences will demonstrate your business understanding.
Next, in a second paragraph, write how you were able to make a data science operationalization of the problem. For example, you might say that in order to help solve this problem you set out to build a classification ML model in order to automate some process.
Third, you then write what you did on the project that is a bit more technical.
Here you might say that you took data from here and make it a link to the original data and then ran a list of models you ran here in your analysis.
Then end with one sentence that picks what your best model was and how it performed.
Lastly, you say in one or two sentences why this matters. For example, now as opposed to before this data analysis, you can now predict X better than Y.
The goal of this project was to create a regression/classification model that was able to predict what you set out to do.
If you are able to swap out the text here with what your case example is you will demonstrate the following:
- You get why what you're doing 'matters'
- You are able to take ill defined problems and turn them into something a data scienst can solve
- You show off your analystical and modeling chops.
- You are able to communicate technical things you do.
Below your Executive Summary, you can document whatever you feel would be of interest to a future employer. Here I would especially suggest diving a bit deeper into your methodology and including images that you are proud of from the project. Remember, that people will probably judge your github project page within 45 seconds tops, you want it to look as clean as possible.
Write documentation that looks like someone you would want to work with.
Image taken from
seaborndocumentation
DO NOT PUT THE GOOD BITS OF YOUR PROJECT BURRIED AWAY AT THE BOTTOM OF YOUR README, YOU ARE NOT WRITING A DETECTIVE NOVEL