Thom Hopmans - The Marketing Technologist | The marketing technology blog

Thom Hopmans

Using AWS Lambda and Slack to have fun while saving on EMR costs

Using AWS Lambda and Slack to have fun while saving on EMR costs

We all have these times where we hack a piece of code together in 5 minutes. Usually, these pieces of code are not hidden gems, they tend to do simple stuff. Every once in a while though, you will find yourself writing a simple script which gives you a big

Helping our new Data Scientists start in Python: A guide to learning by doing

Helping our new Data Scientists start in Python: A guide to learning by doing

The Data Science team at Greenhouse Group is steadily growing and continuously changing. This also implies new Data Scientists and interns starting regularly. Each new Data Scientist we hire is unique and has a different set of skills. What they all have in common though is a strong analytical background

Upload your local Spark script to an AWS EMR cluster using a simple Python script

Upload your local Spark script to an AWS EMR cluster using a simple Python script

Apache Spark [http://spark.apache.org/] is definitely one of the hottest topics in the Data Science community at the moment. Last month when we visited PyData Amsterdam 2016 [http://pydata.org/amsterdam2016/] we witnessed a great example of Spark's immense popularity. The speakers at PyData talking about Spark had

A recommendation system for blogs: Content-based similarity (part 2)

A recommendation system for blogs: Content-based similarity (part 2)

In this second post in a series of posts about a content recommendation system for The Marketing Technologist (TMT) website we are going to elaborate on the concept of content-based recommendation systems. In the first post [https://www.themarketingtechnologist.co/building-a-recommendation-engine-for-geek-setting-up-the-prerequisites-13/] we described the benefits of recommendation systems and we

A recommendation system for blogs: Setting up the prerequisites (part 1)

A recommendation system for blogs: Setting up the prerequisites (part 1)

The goal of data science is typically described as creating value from Big Data. However, data science should also meet a second goal, that is, avoiding an information overload. One particular type of projects that really meet these two goals are recommendation engines. Online stores such as Amazon but also

Slashception with regexp_extract in Hive

As a Data Scientist I frequently need to work with regular expressions. Though the capabilities and power of regular expressions are enormous, I just cannot seem to like them a lot. That is because when they do not function as expected they can be a really time-consuming nightmare. In this

The GAM approach to spend your money more efficiently!

In an earlier blogpost [http://geek.bluemangointeractive.com/optimize-media-spends-using-s-response-curves/] we described how Blue Mango Interactive optimizes the media spend of clients using S-curves. S-curves are used to find the S-shaped relationship of a particular media driver on a KPI such as sales. Moreover, when a S-curve is obtained, we can

Optimizing media spends using S-response curves

A key focus of our Data Science team is to help our clients understand how their marketing spend affects their KPIs. In particular, we create models to understand the effect of individual marketing channels such as television or paid search ads on KPIs such as sales, visits and footfall. Knowing