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I’ve been trying to understand gradient boosted trees on and off for the last few weeks, and it was a surprisingly frustrating exercise trying to find the answer to this question since introductions skimmed over it.

The general boosting algorithm is fairly intuitive and is covered in a lot of places, but the part that no-one seemed to explain was how to fit a single tree to minimize an arbitrary differentiable loss function.

The answer was to be found in Elements of Statistical Learning Second Edition on page 358-9 in sections Steepest Descent and Gradient Boosting (Note how it’s 22…

Keras should be getting a transparent data-parallel multi-GPU training capability pretty soon now, but in the meantime I thought I would share some code I wrote a month ago for doing data-parallel training without making any changes to your model definition.

As a preface to this, I would like to note that your model may not run any faster on multiple GPUs if you are not actually GPU bound; some cases where this can happen include when you use a generator with your data and it‘s creation is CPU/IO bound, or if your model is not particularly complex and you…

If you’ve ever tried playing with Deep Learning, you’ll have found out that you’re not going to get very far without a GPU, and if you didn’t already happen to have an NVIDIA card, you’re going to be left with a choice between spending many hundreds of dollars up front or renting a GPU from a cloud provider.

Renting from a cloud provider will be more expensive in the long run, I’ve personally spent about a hundred dollars in spot instance costs so far, but if you’re not sure how long you’re going to stick with this and you’re not…

Early this year, I tried to brainstorm ways to defeat phishing, and recall asking myself why no-one was doing something like Password Alert because it seemed so simple and so obvious. In June, I found out that Google had already been doing it for years internally and had expended the effort to release their extension both for regular users and enterprises who wanted to deploy it internally.

I was both a bit bummed that someone had beaten me to the punch, but also vindicated that the idea had some merit. …


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