Boyan Angelov

Hire This Expert

About Me

Boyan Angelov leads the machine learning efforts at a Berlin startup, building an AI to help tech companies get better candidates. He has started using machine learning during his work on microbial metagenomes at the Max Planck Institute for Marine Microbiology. The discoveries he made there were in the applications of dimensionality reduction methods. Later he worked in the clinical trials space, focusing on information retrieval and natural language processing.  

Optimal Tooling for Machine Learning and AI

Tooling is probably the least exciting topic in data science at the moment. People seem to be more interested in speaking about the latest chatbot technology or deep learning framework. This just does not make sense. Why would you not dedicate enough time to pick your tools carefully?

Working with Missing Data in Machine Learning

Missing data are probably the most widespread source of errors in your code, and the reason for most of the exception-handling. If you try to remove them, you might reduce the amount of data you have available dramatically — probably the worst that can happen in machine learning.

The Harvard Innovation Lab

Made in Boston @

The Harvard Innovation Lab


Matching Providers

Matching providers 2
comments powered by Disqus.