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Porto Seguro Challenge - 2nd Place Solution
We are pleased to announce that we got second place in the Porto Seguro
Challenge, a competition organized by the largest insurance company in Brazil.
Porto Seguro challenged us to build an algorithm to identify potential buyers of
their products. If you are interested in knowing how to do the same and still
discover the secrets that led us to second place, read on below!
Introduction
In this problem, Porto Seguro provided us with data of users who bought or did
not buy one of its products. T
Consumer vs Server-Grade Hardware and why you can't do Business-Grade work with the formerIn any market or industry, quality work at scale requires purpose-built
high-performance tools.
In a previous article (The Eight Challenges You'll Face With On-Premise
Artificial Intelligence
[https://amalgam.ai/posts/the-eight-challenges-youll-face-with-on-premise-artificial-intelligence/]
), we promised to cover this topic more in-depth in a separate post. Well, we
like to keep our promises, so here we are.
It turns out that 3 of the Challenges we listed (Servers, Networking, and
Storage) ar
Distributed learning in an on-premise cluster - A Kaggle Reinforcement Learning case
Have you tried any distributed learning algorithms? If you are just starting out
in this area, I have my doubts, but if you have been on this path for a few
years, you might have faced one of those models. The incredible development of
the machine learning area in the last decade has not only brought a new state of
the art to several problems but has also taken processing optimization and
parallelization to another level. With increasingly larger models, any common
machine or even a single sup