The Ultimate Tour

Here’s an example of using web services to source data & processing from 3rd parties.  I queried Yelp for top venues, used Google Maps to retrieve a distance matrix.  I then used an R package TSP to calculate the optimal route.  Finally plotting the route on Google Maps.

I presented this at ManchesterR in Feb-15.  Code walk-through can be found on Rpubs 

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Predictive Analytics slides from Nov-14 SQL Sat London

Here are my slides from the Predictive Analytics talk I gave in Nov 14 at the top of Smithfield Meat Market in London.  What a memorable day that was.

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Data Analysis prep with Linux Mint & R

When I embarked on learning R last year I decided to jump whole heartedly into the open source stack with Linux, using a virtual machine running Linux Mint.

There were various reason for this such as productivity with the terminal and easier access to Linux data sources, not to mention, it’s much easier to deploy R scripts with Linux.

During my Data Analysis adventures I found I had to customise Linux to make it more suitable for Data Analysis with R.

I had to rebuild the VM this week, don’t ask! Of course I had to scratch around for the configs again.

Here are the steps I used to get Mint 17.1/Ubuntu 14.04 LTS, primed for Data Analysis with R.

From the terminal :

1. Install the latest version of R, Git, sqLite and libraries that I’ve found are required for data & web munging. Be sure to change to the url to your local mirror found on this page.

sudo add-apt-repository "deb http://cran.rstudio.com/bin/linux/ubuntu trusty/"
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install r-base r-base-dev r-cran-rodbc libxml2-dev libcurl4-openssl-dev git-core sqlite3

3. Set up git

git config --global user.name "Your Name"
git config --global user.email "your@email.com"

2. Install R Studio. You’ll have to change the url for later versions if required.

cd ~
wget http://download1.rstudio.org/rstudio-0.98.1091-amd64.deb
sudo dpkg -i rstudio-0.98.1091-amd64.deb
sudo rm rstudio-0.98.1091-amd64.deb

This should get you going. I’ll add to this if I discover any new config on my travels.

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Johns Hopkins and Coursera MOOC review : Data Science

When I started learning R as a means to boost my analytical skills I was hit by the steep learning curve despite having half-decent coding skills.  I needed to dig deep.

After a couple of books and blogs I was off the starting line but it soon became clear that this was going to take more effort.

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Can I stand on your shoulders?

Sometimes we bump into problems that we can’t solve on our own.  When this happens you can walk away defeated or think of it as an opportunity to learn something new and gain an understanding of your limits.

There are many ways to learn but the one I find most effective is learning to solve a specific problem by engaging with the community.
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