Michał Dyrda - Data Science @ PMI – Journey from business problem to the data product industrialization
Data Science is not a one-man show. It is a team effort that requires every team member to master the tools of the trade. This is extremely important for effectively putting data science to work in a global organization. We introduced the best practices to start, develop and ship data science products, which are currently in use by 30+ data scientists across three different locations, where data science labs of PMI were established in 2017.
We inherited the technologies (e.g. Kubernetes, Docker, Jenkins) and methods (CI/CD with GitFlow) from software engineering, which are helping us in creating data science products starting from the business requirement, through proof of concept up to the industrialization phase. Uses cases which we are developing provides transparency and reproducible in each state of development.
Currently, we provided tens of tangible uses cases results to the business users.
One of the examples is Duty-Free Portfolio Optimization.
Have you ever wondered what is behind the choice of products available on the store shelves? Why at the given airport you can buy different products than at the train station? In this talk I would like to show you technics and tools, which are used in the portfolio optimization problem at Philip Morris International, allowing us to progress towards a smoke-free future. Moreover, during this talk, I will also share our best practices to develop and ship data science products towards production.
Jarek Pałka - If everything seems under control, you just aren't going fast enough.
Did you ever wonder what you need to do to make your code run faster? Have you ever wondered how to become a "performance man"? Perhaps you deal with a performance from time to time, from one failure to the next "severity 1" incident? And you have this weird feeling that you are doing it wrong? Maybe you've never bothered how fast your code runs. It has been known for ages that this is always a database problem (or someone else's problem). Or maybe it's just hard to admit that you don't know how to improve your code?
In this presentation, I will show you how to become a programmer aware of the performance of your code. Accompanied by tools such as JMH, JFR and flame graphs. We will focus not only on tools but also on the process of optimizing performance. We will talk about how good quality, the so-called Clean code affects performance, why the data sets we use are crucial, and when more is not faster.
Watch the video:
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