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ML / AI / Big Data [clear filter]
Friday, January 25
 

10:00am CET

Setting Up AI/ML with Red Hat Infrastructure
In this workshop you will learn how to deploy and configure a software stack in OpenShift for AI and ML workloads. We will cover the setup of Jupyter notebooks on OpenShift, using Ceph Object Storage as a data lake for big data, and the setup and operation of compute environments such as Spark and TensorFlow. By the end of the workshop you will have an environment that can be used by data scientists and data engineers.

Requirements:
* You will need a laptop with a web browser

Speakers
avatar for Sherard Griffin

Sherard Griffin

Senior Manager, Red Hat
Sherard Griffin is a Senior Manager at Red Hat. His primary responsibility is the architecture and development an enterprise-grade AI-as-a-service platform on Kubernetes. Sherard is also responsible for the deployment of Red Hat’s internal AI-as-a-service platform where hundreds... Read More →
avatar for Václav Pavlín

Václav Pavlín

Architect, AI CoE, Office of the CTO, Red Hat Czech
Red Hatter for almost 6 years, working with containers for 5 years, making AI/ML simple, proud Brnonian and Czech


Friday January 25, 2019 10:00am - 11:50am CET
Red Hat Lab - Q305

11:00am CET

Thoth - how to recommend the best possible packages for your application
Having libraries in your Python project properly locked to a specific version is a well known best practice. Dependency management tools in the Python ecosystem lock dependencies to the latest version available, but what if the latest version available is not the best fit for your application? Open source project Thoth is an advanced Python dependency resolver which recommends libraries for your project based on observations that are gathered for Python libraries in specific runtime environments. How these recommendations look like? How are different observations like performance characteristics of machine learning libraries for a particular hardware gathered?

Speakers
avatar for Christoph Görn

Christoph Görn

Principal Software Engineer, Red Hat


Friday January 25, 2019 11:00am - 11:50am CET
R211 - Students Club

12:00pm CET

Data Engineering Environments
This workshop will introduce setup and operation of data engineering environments which allow to process data with easy configuration and at scale to feed the appetite of the data scientists and the models they create. We will cover environments such as Pandas and Spark.

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
avatar for Diane Feddema

Diane Feddema

Principal Software Engineer, Red Hat
Diane Feddema is a principal software engineer at Red Hat Inc Canada, in the AI Center of Excellence. Diane is currently focused on developing and applying machine learning techniques for performance analysis using hardware accelerators, automating these analyses and displaying data... Read More →


Friday January 25, 2019 12:00pm - 1:50pm CET
Red Hat Lab - Q305

2:00pm CET

Machine Learning workflows on Kubernetes with Kubeflow
As Machine Learning requires more and more computational power, scheduling the workload on top of a distributed compute-cluster becomes more attractive. Fortunately, Kubernetes and OpenShift is a great container orchestrator and Kubeflow is a set of tooling running on this platform to help data-scientists to focus on ML problems and not on managing resources. This workshop will guide you through the available components of Kubeflow that take your ML work from the experimentation phase to distributed training and finally serving a model for inference.

This workshop will be limited to 20 attendees. Please bring your own laptop with a recent version of the OpenShift client installed (preferably 3.10 at a minimum).

Speakers
avatar for Marcel Hild

Marcel Hild

Engineering Manager, AI CoE, CTO Office, Red Hat
Marcel Hild has 25+ years of experience in open source business and development. He co-founded a Linux consulting company, worked as a freelance developer, a Solution Architect for Red Hat and core Developer for Cloudforms, a Hybrid Cloud Management tool. Now he researches the topic... Read More →
avatar for Peter MacKinnon

Peter MacKinnon

Principal Software Engineer, Red Hat Inc.
Pete MacKinnon is a Principal Software Engineer in the AI Center of Excellence at Red Hat. He is actively involved in the Kubeflow and Open Data Hub open source projects. He works closely with Red Hat customers and partners to successfully bring their machine learning and analytics... Read More →



Friday January 25, 2019 2:00pm - 3:50pm CET
Red Hat Lab - Q305

4:00pm CET

Introduction to ML techniques
In this workshop, we'll do a deep-dive into some frequently used ML techniques. Using some example datasets, you will learn how data is preprocessed, models trained and then inspected to ensure meaningful conclusions are drawn. You will also get exposed to underlying assumptions of various techniques and how that informs data analysis and preparation. Some programming experience is needed since we will go into details of writing the models in Python.

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


Friday January 25, 2019 4:00pm - 5:50pm CET
Red Hat Lab - Q305
 
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

9:30am CET

Using Machine Learning to find Linux bugs
I’d like to show you how to find bugs in Linux systems using machine learning, when paired with the totally seemingly useless and annoying false positives that come out of your integration tests.

We’ve all been frustrated unreproducible bugs in Linux … And also by stupid test-flakes that show up as failures in integration tests even though nothing related has changed. I want to prove that both of these are the same thing.

Lets take a look at how the Cockpit project trains bots to correlate these flakes into unsupervised clusters. and automatically make use of the data, identifying real bugs, or simply retriggering tests.

We’ll dive into details about Normalized Compression Distance, Unsupervised Clustering, TF-IDF and many other simple techniques used to zero in on the bugs.

Speakers
avatar for Stef Walter

Stef Walter

Hacker, manager, and CI freak., Red Hat
Stef is an avid open source hacker. He's contributed to over a hundred open source projects, and can be found preaching about continuous integration and working on the Cockpit Linux admin interface. He's a usability freak. Stef lives in Germany, and works at Red Hat.



Sunday January 27, 2019 9:30am - 10:20am CET
D105

9:30am CET

Recommendation engines explained
Many of the applications you use and love provide personalised experiences to their users. This hands-on workshop will introduce the basics of recommendation as a class of machine-learning problems, introduce collaborative filtering algorithms, which are a popular way to capture the commonality between users’ interests, and explain how these algorithms work. You’ll learn practical details of using recommendation in your own applications, including: data preparation, tuning the training process to get the most out of recommendation engines, scaling training out with Apache Spark, handling both explicit data (e.g., ratings) and implicit data (e.g., page views or play counts), training and scoring models against streaming and batch data.

Speakers
avatar for Rui Vieira

Rui Vieira

Red Hat
Rui is a Software Engineer at Red Hat working on Data Science, Apache Spark and Spark Streaming applications.
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 →


Sunday January 27, 2019 9:30am - 11:20am CET
C228

10:30am CET

AIOps: Anomaly detection with Prometheus
As IT operations become more agile and complex, at the same time the need to enhance operational efficiency and intelligence grows. Monitoring applications and kubernetes clusters with Prometheus has become quite common. Yet identifying relevant metrics and thresholds for your setup is getting harder.

In this talk, Marcel will show the tooling used to collect and store metrics gathered by Prometheus for the long term. Then analyze those on a large scale using Spark. This includes extracting trends and seasonality but also forecasting of expected values for a given metric. Finally, he will integrate the predicted metrics back into the Prometheus monitoring and alerting stack to enable dynamic thresholding and anomaly detection.

Speakers
avatar for Marcel Hild

Marcel Hild

Engineering Manager, AI CoE, CTO Office, Red Hat
Marcel Hild has 25+ years of experience in open source business and development. He co-founded a Linux consulting company, worked as a freelance developer, a Solution Architect for Red Hat and core Developer for Cloudforms, a Hybrid Cloud Management tool. Now he researches the topic... Read More →



Sunday January 27, 2019 10:30am - 11:20am 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

11:30am CET

radanalytics.io streaming applications workshop
Stream processing at scale, continuous query processing, adding intelligent APIs to streaming applications, preparing data for NLP, using pretrained NLP and sentiment analysis models.

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 →
avatar for Michael McCune

Michael McCune

Principal Software Engineer, Red Hat, Inc.
Michael is a software developer creating open source infrastructure and applications for cloud platforms. He has a passion for problem solving and team building, and a lifelong love of music, food, and culture.


Sunday January 27, 2019 11:30am - 1:20pm CET
C228

12:30pm CET

Kubeflow: ML on OpenShift
Kubeflow is an open source project that has quickly emerged as the de-facto machine learning toolkit for Kubernetes. Kubeflow aims to provide stability, composability, and portability for machine learning by leveraging Kubernetes and other ecosystem projects to implement the infrastructure required to deliver a comprehensive ML platform for data scientists and DevOps engineers alike. This talk will explore the origins of the project, its core architecture, and integration with complementary projects such as JupyterHub, Pachyderm, and SeldonIO. We will examine the user experience, from deployment to notebooks. The presentation will also discuss its relevance to OpenShift and how the emerging popularity of the Operator SDK can expand the capabilities of Kubeflow.

Speakers
avatar for Peter MacKinnon

Peter MacKinnon

Principal Software Engineer, Red Hat Inc.
Pete MacKinnon is a Principal Software Engineer in the AI Center of Excellence at Red Hat. He is actively involved in the Kubeflow and Open Data Hub open source projects. He works closely with Red Hat customers and partners to successfully bring their machine learning and analytics... Read More →



Sunday January 27, 2019 12:30pm - 1:20pm CET
D105

1:30pm CET

Data sketching workshop
time-and-space efficient structures for summarizing data at scale (Bloom filter, count-min sketch, hyperloglog, minhash, t-digest, direct applications to real-world problems, indirect applications to ML, e.g., in feature engineering and synthetic data generation.

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 →
avatar for Erik Erlandson

Erik Erlandson

Principal SW Engineer, Red Hat


Sunday January 27, 2019 1:30pm - 3:20pm CET
C228

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