Anders E. Nielsen
I am an ambitious data professional with a background in computational biology and experience applying data technology to the domains of biotech, supply chain, and manufacturing. I have a strong focus on applying data, ML, statistics, and modern data tools to solve real-world problems.
Projects
Bayesian Biochemistry
Building bespoke Bayesian models for for dose-response curves in biochemical assays.
Bayesian Optimisation Tools and Tutorials
Tools and tutorials for Bayesian optimisation.
Industrial IoT with AWS and Python
Getting started with industial Internet of Things using AWS IoT and Greengrass. From the first sensor to machine learning at the edge.
Posts
Initial Designs for Bayesian Optimisation
Overview of initial design strategies for Bayesian optimisation. Implementations in R.
Test Functions for Bayesian Optimisation
Overview of some functions for testing and benchmarking Bayesian optimisation. Implementations in R.
Alternative Surrogate Models for Bayesian Optimisation
Surrogate model alternatives to Gaussian processes for Bayesian optimisation. Implementations in R.
Acquisition Functions for Bayesian Optimisation
A comprehensive overview of acquisition functions for Gaussian processes and Bayesian optimisation. Implementation in R.
Kernels for Gaussian Processes
A comprehensive overview of kernels, or covariance functions, for Gaussian processes and Bayesian optimisation. Implementation in R.
Bespoke Bayesian Model for Batch Effects in High Throughput Biochemical Assays
Developing a bespoke Bayesian model for dose-response screening assays with batch effects
Bayesian Optimisation from Scratch in R
All the basic components of Bayesian optimisation introduced and implemented in R
Bespoke Bayesian Model for Biochemical Assays
Developing a bespoke Bayesian model for fitting the Hill equation in biochemical assays
Olympic Athletes over Time - A Tidy Bayesian Data Exploration
Exploring a dataset of Olympic athletes over time using Bayesian data analysis and the Tidyverse
Create a website with Wowchemy and Hugo
How I built this website using R Blogdown and the Wowchemy theme for Hugo.
Bespoke Bayesian Model for High Throughput Biochemical Assays
Developing a bespoke Bayesian model for high throughput screening assays
Build an Edge with Greengrass
In this tutorial, we build an IoT edge with Greengrass.
Machine Learning at the Edge and other Advanced Features of Greengrass
In this tutorial, we deploy and operate a machine learning model, in an IoT network at the edge with Greengrass.
Publishing and Subscribing with AWS IoT
In this tutorial, we will take a closer look at the pub/sub model of MQTT and demonstrate its usefulness by having a sensor publish data and change behaviour in response to subscribed messages.
Publishing Industrial Data with AWS IoT
In this tutorial, we will obtain a value from a sensor and publish it to a topic on AWS.
Thing Shadows with AWS IoT
In this tutorial, we discuss the usefulness of thing shadows in industrial IoT, by demonstrating how it keeps the pub/sub network alive even if the thing intermittently goes offline.