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Books

I write

I was lucky enough to be part of a few book projects. This is where I keep them.

Book Cover of ML Validation e-book by Jesper Dramsch

Make Machine Learning work in the Real World

e-Book

I wrote a small ebook about applying validation techniques to different types of real-world datasets. Going into short examples how different data types have to be treated to avoid overfitting.

I touch on the topics of:

  • overfitting
  • train-test splits
  • cross-validation
  • stratification
  • spatial validation
  • temporal validation
  • production models
  • data drift

I made it complementary with a newsletter subscription to my weekly machine learning newsletter. Subscribe to receive insights from Late to the Party on machine learning, data science, and Python every Friday.


Book Cover of Craft Great Resumé Points for Data Jobs

Craft Great Resumé Points for Data Jobs

e-Book

I transitioned from geophysics into data science & machine learning successfully. For my newest Skillshare class, I created a small e-book that details how to translate skills in great bullet points on data science resumés.

Translate those skills you have into something that will get you out of the discard pile and in front of recruiters. Most people taking my classes already have data skills but need some hints to get those into a format recruiters like and understand.

Check out my latest class to get you that job!

Craft your Resumé for Your Career Transition into Data Science & Machine Learning


Book Cover of Advances in Geophysics Vol. 61

70 Years of Machine Learning in Geoscience in Review

Book Chapter

I was invited to write a review about the history of machine learning for Advances in Geophysics. I reviewed the historical co-development of machine learning and geoscientific techniques. A particular focus is laid on Gaussian Processes (Kriging) and Neural Networks.

I read and analyzed over 300 papers for this work, featuring a selection throughout the manuscript.

Modern applications are illustrated with reproducible code examples.

This discussion of modern deep learning also ventures into specific components including:

  • dense neural networks
  • convolutional neural networks
  • recurrent neural networks

Including significant architectures that developed and were applied in this time. The review does not yet include the transformer architecture as it was barely used in geoscience (and the chapter got long enough as is).

There is a preprint version and the typeset version available.


Book Cover of PhD Thesis by Jesper Dramsch

Machine Learning Geoscience

PhD Thesis

This is my PhD thesis. Does it count as a book?

It's 300 pages long and took a bunch of work.

So let's say maybe.

All the code is open source and it's fully published as a website, where you can also find the PDF version and the video of my PhD defense.


Book Cover of 52 things in Geology

52 Things You Should Know About Geology

Book Chapter

This feels like it was ages ago. I wrote a blog post on the ethics of working in oil and gas.

That was made into a small book chapter.

I'm not sure how strongly I hold these beliefs today, seeing the negative impact of corporations on our climate.

You can pick up a copy, but the other essays are probably more entertaining.