Past Meetup

Probabilistic Programming and Data Pipelines

This Meetup is past

83 people went

Location image of event venue

Details

We are very happy to announce our first meetup of 2019! We have had a great first year, and we look forward to putting on more events this year.

This event will take place at Tramshed Tech (tramshedtech.co.uk) on Wednesday 13th February, kindly sponsored by AMPLYFI (amplyfi.com) who are providing us with the venue together with food and refreshments. And of course, we are offering free beer, soft drinks and pizza.

The venue will open at 18:30 when drinks will be provided. The talks will then begin at 19:00 with a break in between for refreshments. After the event, we will be heading to a pub that is en route to Cardiff Central Station.

We can also hold a Lightning Talk session ⚡ if anyone would like to give a short presentation. This is a fantastic opportunity for anyone who is new to presenting, and would like to talk in a welcoming environment. Please let us know if you are interested by filling out this short form: https://goo.gl/forms/uIu5hiCHkgnkTouA2

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Talk 1: Rhys Green - Bayesian Machine Learning in Python

This talk will be a practical introduction to the topic of probabilistic programming in Python using Bayesian Machine Learning techniques. The recent developments in computational performance have allowed for this type of analysis to be performed, making use of techniques such as Monte Carlo-Markov Chain (MCMC) sampling, and Variational Inference (VI). This talk will provide a brief theoretical background, but the majority of the session will be demonstrating the Python code in Jupyter notebooks.

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Talk 2: Gatis Seja - Creating Data Pipelines in Python

Data pipelines are necessary for the flow of information from its source to its consumers, typically data scientists and software developers. Managing data flow from many sources is a complex task where the maintenance cost limits the scale of being able to build a large reliable data warehouse. This presentation proposes a number of applied data engineering principles that can be used to build robust easily manageable data pipelines and data products. Examples will be shown using Python on AWS.

In order to provide a comfortable and welcoming event for all, the evening will be covered by the official PyData Code of Conduct: https://pydata.org/code-of-conduct.html