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Lars Hulstaert

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May 2, 2019

Achieving a top 5% position in an ML competition with AutoML

AutoML pipelines are a hot topic. The general goal is simple: enable everyone to train high-quality models specific to their business…

Achieving a top 5% position in an ML competition with AutoML

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Mar 14, 2019

Machine learning interpretability techniques

Most machine learning systems require the ability to explain to stakeholders why certain predictions are made. When choosing a suitable…

Machine learning interpretability techniques

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Jul 20, 2018

Common data science pitfalls and how to avoid them

During my studies I had the opportunity to work on several machine learning research projects. These projects ranged from studying…

Common data science pitfalls and how to avoid them

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Jul 11, 2018

Understanding model predictions with LIME

In my previous post on model interpretability, I provided an overview of common techniques used to investigate machine learning models. In…

Understanding model predictions with LIME

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Apr 23, 2018

Going deep into object detection

With recent advancements in deep learning based computer vision models, object detection applications are easier to develop than ever…

Going deep into object detection

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Mar 28, 2018

Going deep into image classification

Learning about the different network architectures for image classification is a daunting task. In this blog post I will discuss the main…

Going deep into image classification

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Feb 20, 2018

Interpreting machine learning models

Regardless of the end goal of your data science solutions, an end-user will always prefer solutions that are interpretable and…

Interpreting machine learning models

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Jan 22, 2018

Applying transfer learning in NLP and CV

In this blog post I will discuss two applications of transfer learning. I will provide an overview of examples in the field of natural…

Applying transfer learning in NLP and CV

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Jan 22, 2018

Transfer learning: leveraging insights from large data sets

In this blog post, you’ll learn what transfer learning is, what some of its applications are and why it is critical skill as a data…

Transfer learning: leveraging insights from large data sets

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Dec 20, 2017

Gradient descent vs. neuroevolution

In March 2017, OpenAI released a blog post on evolution strategies, an optimisation technique that has been around for several decades. The…

Gradient descent vs. neuroevolution

Lars Hulstaert

Lars Hulstaert

Data Scientist at J&J, ex-Microsoft. Previously Masters student at Cambridge, Engineering student in Ghent. I like connecting the dots.

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