index.Rmd

---
title: "Portfolio"
output:
  rmdformats::html_clean:
    highlight: kate
---


```{r setup, echo=FALSE, cache=FALSE, warning=FALSE}
library(knitr)
library(rmdformats)

## Global options
options(max.print="75")
opts_chunk$set(echo=FALSE,
               cache=TRUE,
               prompt=FALSE,
               tidy=TRUE,
               comment=NA,
               message=FALSE,
               warning=FALSE)
opts_knit$set(width=75)
```

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```{r, echo=FALSE}
# htmltools::img(src = knitr::image_uri(file.path(R.home("doc"), "html", "logo.png")), 
#                alt = 'logo', 
#                style = 'position:absolute; top:0; right:0; padding:10px;')
```



<style>
div.blue { background-color:#e6f0ff; border-radius: 5px; padding: 20px;}
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## Introduction

Fernando is a data scientist who leverages large datasets and multiple data sources to gain operational insight on public transport systems in London, aiding the build of predictive statistical models that result in improved network reliability.

This Portfolio aims to show both personal and professional projects (when the code can be shared openly).

</div>



*** 


## [Deployment of ML model to detect credit card fraud as microservice](https://github.com/fermumen/credit_card_fraud)
This two part post showcases how R can be used on a professional enviroment to generate production level results. 

[**Part 1**](https://fermumen.github.io/credit_card_fraud/) details how to set up a quick classifier model with extreme gradient boosting and mlr.

[**Part 2**](https://fermumen.github.io/credit_card_fraud/Part_2.nb.html) shows how, with the help of a RESTful API using plumber and docker, we can containeraize our application to be deployed in the cloud to quickly integrate it within our company.



## [bikecommclust](https://github.com/konstantinklemmer/bikecommclust)
Complementary code for "Community structures, interactions and dynamics in London's bicycle sharing network"

_Oct 8, 2018, Ubicom PURBA-2018_

We apply a novel clustering technique to London’s bikesharing network, deriving distinctive behavioral patterns and assessing community interactions and spatio-temporal dynamics. The analyses reveal selfcontained, interconnected and hybrid clusters that mimic London’s physical structure. Exploring changes over time, we find geographically isolated and specialized communities to be relatively consistent, while the remaining system exhibits volatility. We increase understanding of the collective behavior of the bikesharing users.

**Blog Post** - [Medium @ Towards Data Science ](https://towardsdatascience.com/community-structures-interactions-and-dynamics-in-londons-bicycle-sharing-network-using-r-8d5a575c302?source=email-16dab367f3c-1575994848777-layerCake.autoLayerCakeWriterNotification-------------------------ace4915b_ec79_47dc_926e_7e2d16e32332&sk=0dd3fbe12e16d383489f6f08774c760c)

## [saturnR](https://fermumen.github.io/saturnR-docs/)
The package saturnR is a thin wrapper around some complex system calls that automate highway model builds as well as data extraction for output processing on the SATURN software.
[Github page](https://github.com/fermumen/saturnR) (Private)

## [spellbook](https://github.com/fermm92/spellbook-fmm)
Collection of misc functions used across different projects as an R package facilitating reusing bespoke code on transport analysis and time series tasks.


## [Simplex Optimisation](https://github.com/fermm92/simplex-prestressed-beam)
Companion code for essay: "Optimum Design of Prestressed Beams under Uncertainties in the Tendon Layout" (2015)
While not exactly reproducible showcases an implementation of linear optimisation algorithms on FORTRAN with multiple constrains. While the techique is admidetly not the best suited for such a non-liear problem it's a great example on linear algebra algorithmic implementations.

***
 
 
 
 
 
 
 
 
 
 
 
 

<p style="text-align: center;">
_Fernando Munoz 2019_
</p>


<!-- ## Closed source projects -->
<!-- Some alternative closed source projects include: -->

<!-- * Survey data fusion and analysis to build movement matrices for high profile highway schemes. -->
<!-- * GPS data analysis (traffic master) to calibrate journey times on highway models. -->