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Our resources

Our data experts are happy to share their knowledge with the data community. You'll find the articles they've written on this page. These should help you to leverage the potential of your data. Would you like to know more? Please don't hesitate to reach out.

23 June 2020
Blog: Dealing with abrupt market changes in your analysis - a brief tutorial on time series change point detection
The Covid-19 crisis has an extraordinary effect on global economic activity. After this crisis it will remain important to take this period into account when training machine learning models on histor…
23 June 2020
Blog: Dealing with abrupt market changes in your analysis - a brief tutorial on time series change point detection
The Covid-19 crisis has an extraordinary effect on global economic activity. After this crisis it will remain important to take this period into account when training machine learning models on histor…
08 June 2020
Blog: Writing functional DSLs for business domains
In functional programming, a domain specific language (DSL) is a set of functions that can be composed to solve a specific problem.
26 May 2020
Blog: Improving the security of Data Science containers - Using Docker's seccomp profiles and Linux capabilities features
No one wants to be the person who exposed sensitive information through their container and caused a hefty GDPR fine, right? What then should data scientists do to improve the security of their contai…
20 May 2020
Blog: How to grow as a data science professional - introducing the Skill Stack
Professionals need to grow and develop their skills to advance in their career. That’s not different for a data scientist. There are various skills, all contributing to your impact on the project.
20 May 2020
Blog: How to grow as a data science professional - introducing the Skill Stack
Professionals need to grow and develop their skills to advance in their career. That’s not different for a data scientist. There are various skills, all contributing to your impact on the project.
11 May 2020
Blog: Machine learning models on AWS with the Rendezvous architecture
tl;dr Testing and updating machine learning models can be done safely and systematically using the Rendezvous architecture.
29 April 2020
Blog: AWS Lambda: Comparing Golang and Python
Serverless functions are great for lightweight cloud architecture and rapid provisioning. However, sometimes serverless introduces additional complexity to the deployment process.
07 January 2020
Blog: Hosting workshops on AWS using ECS, EC2 and Terraform
During workshops, I often see participants wrestle with software installation before they can get started.
07 January 2020
Blog: Hosting workshops on AWS using ECS, EC2 and Terraform
During workshops, I often see participants wrestle with software installation before they can get started.
06 January 2020
Blog: Preventing churn like a bandit - with uplift modeling, causal inference, and Thompson sampling
The real goal is to prevent churn, not to predict churn. Thus, we predict the effect of treatments. The transformed outcome technique is helpful.
20 December 2019
Blog: A review of Netflix's Metaflow
tl;dr Metaflow is a framework that alleviates several infrastructure-related pains data scientists experience in their projects.
30 September 2019
Blog: On machine learning team composition
Getting machine learning off the ground requires many skills and capabilities. Some of these skills are related, some are not.
30 September 2019
Blog: On machine learning team composition
Getting machine learning off the ground requires many skills and capabilities. Some of these skills are related, some are not.
13 September 2019
Blog: For effective treatment of churn, don't predict churn
In the business to consumer market, there are two strategies to grow market share: gaining new customers, and retaining existing customers. The latter challenge is referred to as preventing churn.
30 August 2019
Blog: Advanced Pandas: Optimize speed and memory
Nowadays the Python data analysis library Pandas is widely used across the world. It started mostly as a data exploration and experimentation tool but is slowly transitioning to be used in a productio…
11 June 2019
Blog: You don't have enough Analytics Translators, here's why that's a problem
I often get asked the question ‘Why do AI projects fail?’ As a data science consultant, I’ve seen a variety of organizations struggle to make AI work for them.
11 June 2019
Blog: You don't have enough Analytics Translators, here's why that's a problem
I often get asked the question ‘Why do AI projects fail?’ As a data science consultant, I’ve seen a variety of organizations struggle to make AI work for them.
06 May 2019
Blog: From predictive to prescriptive analytics - the benefit of causal diagrams
Suppose you work at as a data scientist at a dating site. Recently more and more customers are closing their accounts (a.k.a. churning).
21 January 2019
Blog: Cost comparison of deep learning hardware: Google TPUv2 vs Nvidia Tesla V100
Google offered us a chance to test their new TPUv2 devices for free on Google Cloud as part of the TensorFlow Research Cloud program.
21 November 2017
Blog: Integrating Pandas and scikit-learn with Pipelines
Scikit-learn and Pandas are both great tools for explorative data science. Both require a bit of practice to get the hang of.
21 November 2017
Blog: Integrating Pandas and scikit-learn with Pipelines
Scikit-learn and Pandas are both great tools for explorative data science. Both require a bit of practice to get the hang of.
29 August 2017
Blog: Machine learning for predictive maintenance: where to start?
Think about all the machines you use during a year, all of them, from a toaster every morning to an airplane every summer holiday. Now imagine that, from now on, one of them would fail every day.