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README.Rmd
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README.Rmd
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---
output: github_document
always_allow_html: true
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
#devtools::install_github('rich-iannone/DiagrammeR')
library(DiagrammeR)
```
<img src='logo.png' align="right" height="44" />
# ML SAM - Machine Learning Stock Assesment Model
This is the formal documentation for the data and code associated with the NSF accelerator project.
## General workflow
Proper coordination between contributors is necessary to ensure a stable code base. To ensure that all major modeling files and supporting functions are up to date it is important to follow the agreed upon workflow.
That workflow is as follows:
1. The `gulfofmaine/MLSAM-collab` repository will be maintained as the "gold-standard" repository. The most up-to-date features can be found there.
2. Contributors should start by setting up their own working branches by forking, then cloning copies of the `gulfofmaine/MLSAM-collab` repository
3. It is then recommended contributors create a "working branch" from which to test new features and code changes. This way, any new updates from the `gulfofmaine/MLSAM-collab` master branch can be pulled safely to personal repositories as needed
4. The `gulfofmaine/MLSAM-collab` repo can then be set as the upstream remote by typing `git add remote upstream https://github.com/gulfofmaine/MLSAM-collab.git` from the terminal when working locally in the forked repositories
5. When features are complete, or when changes to the upstream repository are necessary, they will be added using a pull-request
6. New updates can then be pulled to individual forks using `git pull upstream master` in the terminal
## ML Stock Assesment Model Pipeline
```{r , eval = TRUE, layout = "l-page", fig.align='center'}
overview_viz <- grViz(diagram = "graphviz/model_diagnostics.dot", engine = "dot", width = 800)
overview_viz
```