What we're about

Welcome to the IBM Code Bristol Meetup!

This Meetup group is a learning community for developers run by developers. We primarily offer a series of hands-on workshops (BYOD*) with some extra special events such as mini-conferences and Ask Me Anything sessions on a variety of technologies including:

- Cloud Native Development and Containers
- Internet of Things
- Artificial Intelligence and Machine Learning
- Data Science
- Blockchain

We will run everything from 101 workshops, through intermediate and deeper dives into to a technology with our developer advocates plus special guest developers and engineers from our software labs.

What you can expect during our Meetups? Hands-on, talks, advice and opportunities for asking questions.

We also have Meetup groups in London and Scotland (Edinburgh and Glasgow),

* https://www.meetup.com/ibm-code-london/
* https://www.meetup.com/IBM-Code-Edinburgh/

We hope to see you at our events! **

IBM Developer Advocacy team

* Bring Your Own Device

** We currently run all our events online, but we hope to start live events again soon.

Thanks for your continued support

Missed a session? All content is made available on our GitHub Repro where all the code is there for you: http://ibm.biz/content-code-ldn

Code of Conduct : https://github.com/IBMCodeLondon/infos/blob/master/code-of-conduct.md ( https://github.com/arlemi/IBMCode_London/blob/master/code-of-conduct.md )

Upcoming events (3)

Data Science Lunch and Learn - Modelling COVID data

Online event

This is part 2 of a 4 part series on dealing with COVID case data. Don't worry, you should be able to follow this session by itself and you can always find the replays at https://ibm.biz/data-science-monday When you have a clear picture of your input data you can start looking for effects and relations. In this session we will use current case data and government measures data to start looking into the effects of measures on early outbreaks. Using curve fitting we will derive a measure representing the severity of an outbreak and relate that to government measures using XGBoost. SHAP will be applied to understand the resulting model. This session will dive a bit deeper into data preparation, feature engineering and even a bit of optimization, creating a suitable dataset for modeling. Ever heard of a Gumbel distribution? Join us to find out! We will run a Jupyter notebook in Watson Studio. If you want to try this out for yourself, please go the following link to sign up for a free account: https://ibm.biz/BdqQ4D Then follow these instructions to get up and running: https://github.com/IBMDeveloperUK/data-science-lunch-and-learn/blob/master/watson-studio-instructions.md Presenter: Damiaan Zwietering Host: Margriet Groenendijk JOINING INSTRUCTIONS This event will be live streamed and available on demand via our channel on Crowdcast: https://www.crowdcast.io/e/data-science-lunch-and-2/register Instructions on how to setup your device for Crowdcast can be found here: https://www.crowdcast.io/setup

Code@THINK - A Free Virtual Developer Conference

Online event

Join IBM for an afternoon of educational talks and workshops all for FREE. Agenda: 13.00 - Welcome and Introductory Keynote 13.30 - Tech Talk: Intro to Application Modernisation 14.00 - Workshops: Restful interaction with z/OS from Kubernetes Build and deploy custom AI predictive models 15.30 - Making sense of the written word: A short history of Natural Language Processing 15.55 - Building for Scale: Choirless 16.30 - Workshops: Build reactive Java applications ready for an event-centric world Removing unfair bias is Machine Learning 18.00 - Choirless final performance, closing remarks and Q+A To register and for further details on the agenda please visit the conference website: https://www.ibm.com/uk-en/events/think-summit/codeatthink.html

Data Science Lunch and Learn - Fitting the COVID curves

Online event

This is part 3 of a 4 part series on dealing with COVID case data. Don't worry, you should be able to follow this session by itself and you can always find the replays at https://ibm.biz/data-science-monday During the early stages of the COVID pandemic there was a lot of discussion about flattening the curve, to prevent overload on our health care system. So what exactly is that curve, and how do you fit it to the raw case report data coming in? We will discuss several approaches and show you when and how they work. In addition, we will discuss a novel approach to consider the nature of an outbreak, resulting in a clustering showing the underlying outbreaks in the aggregated data for a region. More advanced stuff, but you should be able to follow with a bit of statistics and high school maths. We will run a Jupyter notebook in Watson Studio. If you want to try this out for yourself, please go the following link to sign up for a free account: https://ibm.biz/Bdq3Lw Then follow these instructions to get up and running: https://github.com/IBMDeveloperUK/data-science-lunch-and-learn/blob/master/watson-studio-instructions.md Presenter: Damiaan Zwietering Host: Margriet Groenendijk JOINING INSTRUCTIONS This event will be live streamed and available on demand via our channel on Crowdcast: https://www.crowdcast.io/e/data-science-lunch-and-3/register Instructions on how to setup your device for Crowdcast can be found here: https://www.crowdcast.io/setup

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