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ML / AI / Big Data [clear filter]
Saturday, January 26
 

4:00pm CET

Container workflows for data science and ML
This talk will introduce the workflows and concerns of data scientists and machine learning engineers and show that OpenShift is a powerhouse for intelligent applications.

We’ll show how community projects like radanalytics.io support the entire intelligent application development lifecycle. You’ll learn about data science workflows and their deep similarities to devops workflows. You’ll see how well scale-out data processing frameworks like Apache Spark work in the cloud.

Operators will learn how OpenShift can support data science and ML workflows. Application developers will learn how OpenShift can enable intelligent applications and cross-functional collaboration. Data scientists will leave with concrete suggestions for how to use open-source tools to make their work more productive.

Speakers
avatar for William Benton

William Benton

Manager, Software Engineering and Sr. Principal Engineer, Red Hat, Inc
William Benton leads a team of data scientists and engineers at Red Hat, where he has applied machine learning to problems ranging from forecasting cloud infrastructure costs to designing better cycling workouts. His current focus is investigating the best ways to build and deploy... Read More →



Saturday January 26, 2019 4:00pm - 4:25pm CET
D105

5:00pm CET

Learning "Learning to Rank"
Excellent recall is insufficient for useful search; search engines also need to identify the most relevant results in a sea of matches. Learning to Rank algorithms aim to capture the relative utility of search results so as to return useful suggestions quickly and efficiently.
In this introductory talk Sophie will explain some Learning to Rank methods, from standard linear regression, to gradient-boosted decision trees, and apply them to a real search engine. She will compare the methods and discuss the pitfalls she ran into when training a Learning to Rank model.
You will walk away from this talk with an understanding of the problems involved in relevant search, an overview of key techniques, and the knowledge needed to implement Learning to Rank algorithms on your own data set.

Speakers
avatar for Sophie Watson

Sophie Watson

Senior Data Scientist, Red Hat
Sophie Watson is a data scientist at Red Hat, where she helps customers use machine learning to solve business problems in the hybrid cloud. She is a frequent public speaker on topics including machine learning workflows on Kubernetes, recommendation engines, and machine learning... Read More →



Saturday January 26, 2019 5:00pm - 5:25pm CET
D105
 
Sunday, January 27
 

9:00am CET

Machine Learning Practical Example
Now that Machine Learning has moved from the esoteric realm and into the world of daily application, what steps are required to prepare existing data to become ML training data sets? What constitutes a good use case? What is the actual cost in effort and time to prepare the data? How much data is required, and what accessible techniques can be applied to achieve that minimum? This session explores the practical steps for non-experts to prepare actual issue tracking data for consumption by ML training algorithms, leveraging available community and Red Hat resources.

Here is a link to the associated video https://www.youtube.com/watch?v=T1sYLbuHBZU

Speakers
avatar for Prasanth Anbalagan

Prasanth Anbalagan

Senior Software Engineer (QE and Analysis), Red Hat, RH - Raleigh - Red Hat Tower
Dr. Prasanth Anbalagan is a Senior Software Engineer (QE and Analysis) on the Artificial Intelligence Center of Excellence Team at Red Hat. As a member of AI team at Red Hat, Prasanth focuses on development of ML services and tools as part of an Analytics, Machine Learning and AI... Read More →
MY

Mark Yarborough

Manager, Red Hat



Sunday January 27, 2019 9:00am - 9:25am CET
D105

11:30am CET

Let's play with Brno Data
Have you heard of the term Open Data? Did you know that Brno provides Open Data? Do you know how to access them, how to handle them? How to properly visualize data and draw conclusions? And actually... what is the use of it? Let's talk Open Data!

The aim of the session is to use Brno Open Data to give concise view to the topics of Open Data and Data Visualization and demonstrate in a popular form how proper visualization and catching story-telling can attract even people of completely unrelated backgrounds.

The workshop `Data Science Workout with Open Data` is connected to this talk and shows basic data wrangling and introduces participants to the basic data-related work by using Open Data.


Presentation (preview only, complete site will be released after the talk) at: https://devconf-brno-data.netlify.com/

Speakers
avatar for Marek Čermák

Marek Čermák

Software Engineer, RH - Brno - Tech Park Brno - B
Among other things, Marek is a data engineer, cloud developer, an open-source enthusiast and a Jupyter hacker. He likes new technologies and the challenges they bring along. He also likes to write and/or talk about the solutions. Marek is currently working as a scientific software... Read More →


Sunday January 27, 2019 11:30am - 12:20pm CET
D105

1:30pm CET

Understanding Neural Networks (Somewhat)
Neural Networks are the first technique everyone thinks about when she considers applying machine learning. But understanding of NNs is usually lacking and the availability of high-level packages does help with this.
Understanding NNs at least somewhat is necessarily to effectively using them. The type of NN used decides what problems can be solved but what works best for a given problem? How to train the network?
This talk gives an introduction to the commonly used NNs, the math behind them, and how to best use them.

Speakers
avatar for Sanjay Arora

Sanjay Arora

Data Scientist
Data scientist at Red Hat
avatar for Ulrich Drepper

Ulrich Drepper

System Research & Data Science, CTO Office, Red Hat
Data Scientist, CTO Office



Sunday January 27, 2019 1:30pm - 3:20pm CET
D105