Practical Deep Learning (talk)

Yesterday at IT Tage 2017, I had an introductory-level talk on deep learning.

After giving an overview of concepts and frameworks, I zoomed in on the task of image classification using Keras, Tensorflow and PyTorch, not aiming for high classification accuracy but wanting to convey the different “look and feel” of these frameworks.

(By sheer chance, the use case chosen happened to be about telling apart different types of endurance sports ;-))

Here are the slides, and here are the Jupyter notebooks.

Thanks to everyone who attended & thanks for reading!

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I’m a developer, why should I care about matrices or calculus? (talk at MLConference 2017)

Yesterday at ML Conference, which took place this year for the first time, I had a talk on cool bits of calculus and linear algebra that are useful and fun to know if you’re writing code for deep learning and/or machine learning.

Originally, the title was something like “What every interested ML/DL developer should know about matrices and calculus”, but then really I didn’t like the schoolmasterly tone that had, as really what I’ve wanted to convey was the fun and the fascination of it …

So, without further ado, here are the slides and the raw presentation on github.

Thanks for reading!