Devoxx UK 2019
from Wednesday 8 May to Friday 10 May 2019.
Mani is a passionate developer mainly in the Java/JVM space, currently strengthening teams and helping them accelerate when working with small teams and startups, as a freelance software engineer/data engineer. A Java Champion, JCP Member, OpenJDK contributor, thought leader in the LJC and other developer communities and involved with @adoptopenjdk, @graalvm and other F/OSS projects. Writes code, not just on the Java/JVM platform but in other programming languages, hence likes to call himself a polyglot developer. He sees himself working in the areas of core Java, JVM, JDK, Hotspot, Graal, GraalVM, Truffle, VMs, and Performance Tuning. An advocate of a number of agile and software craftsmanship practices and a regular at many talks.
See also http://neomatrix369.wordpress.com
As a seasoned and experienced developer, we have many things on our minds like:
- code quality
- the correctness of the solution
- test coverage
- code readability
- software design
- among others…
There are no perfect solutions, but solutions that work, and can be understood and easily changed by others.
Without giving away too much about the outcome and purpose of using the kata, the kata is meant to primarily test and stretch our coding skills -
Specification analysis/interpretation, among other skills as a developer.
At each session, every attempt by a developer opens up new avenues and discussions. We will learn from the questions asked and discussions during the session.
Towards the end of the workshop, we will showcase our code to the rest of the attendees, and explain the rationale of our approach and be able to reason the whys and hows.
We are NOT attempting to complete the kata but learn from our approach(es) and share it with others.
Please come to the workshop with a development environment of your choice (any language/platform, development or testing frameworks, or libraries), a GitHub account, a local git client.
For many of us who are developer turning data scientist, we are always concerned about how to build a model, train it, etc... And yes, we want the best accuracy (close to 99%).
But as every seasoned data scientist will always advise us, we need first and foremost to understand our data, ensure it’s clean and prepared before doing any training on it.
During the conference, we will explore multiple problems occurring during data analysis or preparation and for each a technique to solve them (from a list of them). You will go away with a number of resources to explore at your own pace.
We will cover these categories of problems:
- dirty data
- disparate datasets - needing normalisation
- too much information to process
- and others…
We will cover some of these techniques:
- analysis - detecting misleading data, outliers, specific time series issues
- cleaning - deal with missing/ambiguous values, outliers, generating synthetic data, resampling
- preparation - using statistical and physics functions, dimensionality reduction, feature selection, resampling
And using different kinds of plots relevant at different stages.