data.stage festival.stage tech.stage work.shop(0) work.shop(1)
09:30
Opening of the Data Festival 2019
Alexander Thamm, CEO, Alexander Thamm GmbH | Dr. Carsten Bange, CEO, BARC GmbH
09:30 - 09:45
09:45
How to generate P&L impact with Data Science (EN)
Dr. Carsten Bange, Gründer und Geschäftsführer, BARC GmbH | Dr. Holger Kömm, Director Data Science Lab, Adidas AG
09:45 - 10:15
Keynote
How to generate P&L impact with Data Science (EN)All too often Data Science projects fail to deliver measurable impact on organization’s profit and loss statements. Even successful prototypes do not make it into production when essential success factors like identifying the right cases, establishing a product mindset or focusing on operationalization are ignored. Carsten and Holger share best practices compressed into 10 key aspects that ensure P&L impact for Data Science.
10:00
10:15
Coffee Break
10:15 - 10:45
Coffee Break
10:15 - 10:45
Coffee Break
10:15 - 10:45
10:30
10:45
Making Scout24 ready for AI (EN)
Julia Butter, AI Evangelist, Scout24 AG
10:45 - 11:15
Online Business
Making Scout24 ready for AI (EN)Artificial Intelligence will change the world in the next three years. To keep track with this exponentially growing technology it is important to make everyone in your company ready for AI. Since mid 2018 Scout24 is on a journey to make every Scoutie ready for AI and to prepare the complete business for AI. I will describe our journey, learnings of the last months and present exciting AI projects which help Scout24 to make the difference.
Connecting Intelligences - what we learned developing an Inspirational AI (EN + DE)
Florian Dohmann, CEO, Birds on Mars | Roman Lipski, Artist, Atelier Lipski
10:45 - 11:15
Start-up
The Scout24 Data Platform: a technical deep dive (EN)
Sean Gustafson, Technical Product Manager, Scout24 AG
10:45 - 12:15
Deep Dive
The Scout24 Data Platform: a technical deep dive (EN)The Scout24 Data Platform powers all reporting, ad hoc analytics and machine learning products at AutoScout24 and ImmobilienScout24. In this talk, I will take a technical deep dive into our modern, cloud-based big data platform. I will discuss our evolution of approaches to ingestion, ETL, access control, reporting and machine learning with a focus on in-the-trenches learnings gained from our many failures and successes as we migrated from a traditional Oracle Data Warehouse to an AWS-based data lake.
Building and Deploying Your Image Classification Model in One Hour (EN)
Vincent Houdebine, Data Scientist, Dataiku
10:45 - 12:15
Exclusive Workshop
Building and Deploying Your Image Classification Model in One Hour (EN)During this workshop, you will learn how you can use Dataiku DSS to build a Deep Learning model for Image classification without a single line of code or deep learning expertise. Step by step, you’ll explore different ways to leverage existing state-of-the art deep learning models in your own projects. Throughout the workshop, you will build your own image classifier using a pre-trained model and deploy it to a production environment to perform real-time predictions on images.
TBD
10:45 - 12:15
Exclusive Workshop
11:00
11:15
Using Deep Learning to rank and tag millions of hotel images (EN)
Tanuj Jain, Data Scientist, idealo internet GmbH | Christopher Lennan, Senior Data Scientist, idealo internet GmbH
11:15 - 11:45
Online Business
Using Deep Learning to rank and tag millions of hotel images (EN)At idealo.de (a leading price comparison website in Europe), we have a dedicated service to provide hotel price comparisons (hotel.idealo.de). For each hotel, we receive dozens of images and face the challenge of composing image galleries that are attractive and at the same time help our users to make informed decisions. Given that we have millions of hotel offers, we end up with more than 100 million images for which we need both an attractiveness assessment and a tag (e.g. a “bathroom” or “bedroom” tag)...
Fun with visual similarity search - Content-based image retrieval (CBIR) with Neural Networks (EN)A *brief introduction to CBIR with neural networks*: the general setup and architecture, feature representations, similarity measures, metrics and losses, datasets, different ways of training, common problems, and differences to classic computer vision algorithms. 2. *Lessons learned*: how RoomAR uses CBIR, hands-on implementation of CBIR with PyTorch, speeding up the search, and some (fun) ideas of what you can do with this setup.
11:30
11:45
I Never Meta-Data I Didn't Like (EN)
Colin Clark, Head of Global Data Engineering, WayFair
11:45 - 12:15
Online Business
I Never Meta-Data I Didn't Like (EN)An overview and demonstration of how to use meta-data for data driven ROI.
Know your jump - Uniting NLP and quantitative financial analytics to explain jumps in asset prices (EN)When in 1976, Robert Merton introduced jumps to the modelling of stock prices, he attributed the occurrence of such to
12:00
12:15
Lunch Break
12:15 - 13:45
Lunch Break
12:15 - 13:45
Lunch Break
12:15 - 13:45
12:30
12:45
13:00
13:15
13:30
13:45
Data Ethics (EN)
Alexander Borek, Global Head of Data & Analytics, Volkswagen Financial Services AG | Benno Blumoser, Innovation Head of Siemens AI Lab, Siemens | Prof. Dr. Ulrike Reisach, Commissioner for International Affairs Information Management Department, HNU | Jörg Bienert, Vorsitzender KI Bundesverband, Geschäftsführer aiso-lab
13:45 - 14:45
Panel
Productionizing Machine Learning Models - Lessons Learned in the Hadoop Ecosystem and the Way Ahead (EN)
Steffen Bunzel, Data Scientist, Alexander Thamm GmbH | Simon Weiß, Data Scientist, Alexander Thamm GmbH
13:45 - 15:15
Deep Dive
Productionizing Machine Learning Models - Lessons Learned in the Hadoop Ecosystem and the Way Ahead (EN)The deployment of machine learning models can be challenging. Especially in the context of distributed systems: Python being the dominant language among data scientists creates frictions when integrating with JVM-based tools such as Spark or managing application dependencies on clusters of heterogenous machines. Many data scientists developing on such systems struggle with the subtleties of these challenges. This presentation will share lessons learned working on large-scale Hadoop clusters and examine the most promising approaches to alleviate common issues. In particular, we will discuss our experience with leveraging containerization to tackle the dependency management challenge from a data scientist\\\'s point of view.
HPCC Systems - A Hidden Champion in Big Data Processing (EN)
Fabian Fier | PhD Student | Humboldt-Universität zu Berlin
13:45 - 15:15
Exclusive Workshop
HPCC Systems - A Hidden Champion in Big Data Processing (EN)HPCC Systems is an open-source big data system. It is developed by LexisNexis® Risk Solutions and used for credit ratings, fraud detection, anti money laundering, and many more enterprise applications. The system is based on the query language ECL that gets compiled down to C++ and machine code to be automatically deployed and executed on a compute cluster. In this workshop, we\'ll walk through the architecture of HPCC Systems, its capabilities and popular extensions (ML, visualization, connectors to other systems), and learn basics of its main query language ECL. Users of other big data systems such as Spark or Flink will feel familiar with the dataflow-oriented query language, the data types, and the available operators. However, the workshop is open to everyone interested in the topic without prior knowledge.
TBD
13:45 - 15:15
Exclusive Workshop
14:00
14:15
TBD
14:15 - 14:45
Data Visualization
14:30
14:45
data.networking(0)
Leading Topic: Data Ethics
14:45 - 15:15
Special
A Practical Guide to AI, Machine Learning, and Data Science (EN)
Ian Swanson, Vice President of Product AI/ML | Oracle
14:45 - 15:15
AI in your Enterprise
A Practical Guide to AI, Machine Learning, and Data Science (EN)Eager to adopt AI in your enterprise? Get an inside look at Oracle\'s platform AI solutions including new approaches using machine learning and data science. There is a seismic shift among Enterprises to harness more and more transformational technologies to improve their customer experiences, drive greater revenues, and lower operational costs. In this talk, we will cover Oracle’s strategy and solutions for AI across all of Oracle cloud platform including the pervasive mix of AI, Machine Learning across all of our services portfolio. See new advancements in data science and learn ways to develop and build new AI-based applications. We\'ll hear some of our customer success stories to date, and provide a personal pathway for enterprises to adopt these technologies based on where they are in their transformational journey.
15:00
15:15
Coffee Break
15:15 - 15:45
Coffee Break
15:15 - 15:45
Coffee Break
15:15 - 15:45
15:30
15:45
Peak Spotting — managing the capacity of Germany's long distance rail network with advanced visualisations (EN)
Mathias Richter, Senior Referent Digitale Transformation, DB Fernverkehr | Christian Laesser, Freelance Interaction Designer & Data Visualization Designer, Deutsche Bahn AG | Stephan Thiel, Co-Founder & Managing Director, Studio NAND
15:45 - 16:15
Transport & Industry
Peak Spotting — managing the capacity of Germany's long distance rail network with advanced visualisations (EN)A continuously increasing number of long-distance passengers requires a simple and fast identification of traffic corridors and trains with high load factors. In order to prevent over-utilisation of trains, tabular presentations of forecast and booking figures for individual trains were previously used...
Smart Training of ML Models in Audio- and Video Mining (EN)
Dr. Annina Neumann, VP Data Technology, ProSiebenSat.1 Media SE | Sebastian Schaal, Founder, Luminovo
15:45 - 16:15
Data in Media Companies
Smart Training of ML Models in Audio- and Video Mining (EN)The need for training data for machine learning algorithms is still incredibly high and is constantly growing with the growing use of artificial intelligence. Many companies are therefore faced with the challenge of reluctant to use methods such as deep learning because training the models would be too complex and time-consuming. At the same time, however, models available on the market are usually not directly applicable and do not fit optimally to one\\\\\\\'s own needs...
Demystifying the neural network black box: An interactive session on understanding decisions made by Convolutional Neural Networks (EN)
Tanuj Jain, Data Scientist, idealo internet GmbH Christopher Lennan, Senior Data Scientist, idealo internet GmbH
15:45 - 17:15
Deep Dive
Demystifying the neural network black box: An interactive session on understanding decisions made by Convolutional Neural Networks (EN)Convolutional Neural Networks (CNN) are state of the art when it comes to computer vision tasks, such as image recognition and object detection. However, due to the high amount of architectural complexity, it is often difficult to interpret the decisions made by these networks. Luckily, there are several techniques available which can enhance our comprehension of CNN decisions. These techniques are generally divided into attribution and visualisation methods...
Deep dive into Machine Learning with the Oracle Platform (incl. live demo) (EN)
Mats Stellwall, Data Scientist, Oracle EMEA
15:45 - 17:15
Exclusive Workshop
Deep dive into Machine Learning with the Oracle Platform (incl. live demo) (EN)In this workshop we will do a in-depth walkthrough on how you can use machine learning by a single click as part of your visualizations and analysis, how you can build Machine Learning models using Python/R code with notebooks against Big Data and Relational Data and even how you can do machine learning using good old SQL. Everything using Oracle’s state of the art Cloud Infrastructure.
TBD
15:45 - 17:15
Exclusive Workshop
16:00
16:15
Two years of Data Science in a Fujitsu factory (EN)
Alena Fojtík, Senior Data Scientist, Fujitsu TDS GmbH
16:15 - 16:45
Transport & Industry
Two years of Data Science in a Fujitsu factory (EN)When talking about data science projects we often focus on algorithms and results. But when you start a data science project from scratch in a factory there are a lot of different problems that need to be tackled: where to install a sensor in order to get data, how to involve external parties as the maker of the machines, defining what is acceptable data quality.... In this talk I want to discuss the challenges we faced and what we learned when we used data science in the Fujitsu factory in Augsburg in order to improve run time and quality.
Predictive Road Condition (EN)
Dr. Michael Unterreiner, Projektleiter, Porsche AG
16:15 - 16:45
Data & AI in Automotive
Predictive Road Condition (EN)The driving situations, the dynamic condition of the vehicle and the road condition are of high relevance in order to return the vehicle from critical situations, in particular with adverse weather-related road conditions, into a safe condition. The subject of this presentation is to determine road conditions and to derive a prediction of these with black data.
16:30
16:45
Anomaly detection in customs area (EN)
Michael Beckmann, Tax Manager & IT, Henkel AG & Co. KGaA
16:45 - 17:15
Transport & Industry
Anomaly detection in customs area (EN)The search for anomalous transactions was performed manually on historical data. A check for previously unknown anomalies and attribute constellations is hardly possible with manually defined rules. The aim of the project is to automatically detect anomalies and unwanted deviations using intelligent and learning procedures. The project therefore focused on advanced technologies (e.g. neural networks).
Datenarchitektur für Business Analytics – was Sie berücksichtigen sollten
Jacqueline Bloemen, Senior Analyst, BARC
16:45 - 17:15
Data Architecture
17:00
17:15
Beer Break
17:15 - 17:45
Beer Break
17:15 - 17:45
Beer Break
17:15 - 17:45
17:30
17:45
AI impact on P&L (EN)
Dr. Holger Kömm, Director Data Science Lab, Adidas AG | Alexander Borek, Global Head of Data & Analytics, Volkswagen Financial Services AG | Dat Tran, Head of Data Science, idealo.de | Vidya Munde-Müller, Founder & Ambassador, Women in AI | Marcus Hartmann, Chief Data Officer, ProSiebenSat1 Media SE | Dr. Sébastien Foucaud, Vice-President Data Science, XING
17:45 - 18:45
Panel
Data Science Kickstart in Germany (EN)
Students of ReDI School of Digital Integration | Klaus Roßmann
17:45 - 18:45
Special
18:00
18:15
18:30
18:45
The legendary Data Festival Party
with Drinks, Food & Live Music.
18:45 - 00:00
19:00
19:15
19:30
19:45
20:00
20:15
20:30
20:45
21:00
21:15
21:30
21:45
22:00
22:15
22:30
22:45
23:00
23:15
23:30
23:45

data.stage

festival.stage

tech.stage

work.shop(0)

work.shop(1)

  • TBD
    10:45 - 12:15
  • TBD
    13:45 - 15:15
  • TBD
    15:45 - 17:15
data.stage festival.stage tech.stage work.shop(0) work.shop(1)
10:15
Coffee Break
10:15 - 10:45
Coffee Break
10:15 - 10:45
Coffee Break
10:15 - 10:45
10:30
10:45
Connecting Intelligences - what we learned developing an Inspirational AI (EN + DE)
Florian Dohmann, CEO, Birds on Mars | Roman Lipski, Artist, Atelier Lipski
10:45 - 11:15
Start-up
TBD
10:45 - 12:15
Exclusive Workshop
11:00
11:15
11:30
11:45
12:00
12:15
Lunch Break
12:15 - 13:45
Lunch Break
12:15 - 13:45
Lunch Break
12:15 - 13:45
12:30
12:45
13:00
13:15
13:30
13:45
TBD
13:45 - 15:15
Exclusive Workshop
14:00
14:15
TBD
14:15 - 14:45
Data Visualization
14:30
14:45
data.networking(0)
Leading Topic: Data Ethics
14:45 - 15:15
Special
15:00
15:15
Coffee Break
15:15 - 15:45
Coffee Break
15:15 - 15:45
Coffee Break
15:15 - 15:45
15:30
15:45
TBD
15:45 - 17:15
Exclusive Workshop
16:00
16:15
16:30
16:45
Datenarchitektur für Business Analytics – was Sie berücksichtigen sollten
Jacqueline Bloemen, Senior Analyst, BARC
16:45 - 17:15
Data Architecture
17:00
17:15
Beer Break
17:15 - 17:45
Beer Break
17:15 - 17:45
Beer Break
17:15 - 17:45
17:30
17:45
18:00
18:15
18:30
18:45
The legendary Data Festival Party
with Drinks, Food & Live Music.
18:45 - 00:00
19:00
19:15
19:30
19:45
20:00
20:15
20:30
20:45
21:00
21:15
21:30
21:45
22:00
22:15
22:30
22:45
23:00
23:15
23:30
23:45

data.stage

festival.stage

tech.stage

work.shop(1)

  • TBD
    10:45 - 12:15
  • TBD
    13:45 - 15:15
  • TBD
    15:45 - 17:15
data.stage festival.stage tech.stage work.shop(0) work.shop(1)
09:30
Opening of the Data Festival 2019
Alexander Thamm, CEO, Alexander Thamm GmbH | Dr. Carsten Bange, CEO, BARC GmbH
09:30 - 09:45
09:45
How to generate P&L impact with Data Science (EN)
Dr. Carsten Bange, Gründer und Geschäftsführer, BARC GmbH | Dr. Holger Kömm, Director Data Science Lab, Adidas AG
09:45 - 10:15
Keynote
How to generate P&L impact with Data Science (EN)All too often Data Science projects fail to deliver measurable impact on organization’s profit and loss statements. Even successful prototypes do not make it into production when essential success factors like identifying the right cases, establishing a product mindset or focusing on operationalization are ignored. Carsten and Holger share best practices compressed into 10 key aspects that ensure P&L impact for Data Science.
10:00
10:15
Coffee Break
10:15 - 10:45
Coffee Break
10:15 - 10:45
Coffee Break
10:15 - 10:45
10:30
10:45
Making Scout24 ready for AI (EN)
Julia Butter, AI Evangelist, Scout24 AG
10:45 - 11:15
Online Business
Making Scout24 ready for AI (EN)Artificial Intelligence will change the world in the next three years. To keep track with this exponentially growing technology it is important to make everyone in your company ready for AI. Since mid 2018 Scout24 is on a journey to make every Scoutie ready for AI and to prepare the complete business for AI. I will describe our journey, learnings of the last months and present exciting AI projects which help Scout24 to make the difference.
Connecting Intelligences - what we learned developing an Inspirational AI (EN + DE)
Florian Dohmann, CEO, Birds on Mars | Roman Lipski, Artist, Atelier Lipski
10:45 - 11:15
Start-up
The Scout24 Data Platform: a technical deep dive (EN)
Sean Gustafson, Technical Product Manager, Scout24 AG
10:45 - 12:15
Deep Dive
The Scout24 Data Platform: a technical deep dive (EN)The Scout24 Data Platform powers all reporting, ad hoc analytics and machine learning products at AutoScout24 and ImmobilienScout24. In this talk, I will take a technical deep dive into our modern, cloud-based big data platform. I will discuss our evolution of approaches to ingestion, ETL, access control, reporting and machine learning with a focus on in-the-trenches learnings gained from our many failures and successes as we migrated from a traditional Oracle Data Warehouse to an AWS-based data lake.
Building and Deploying Your Image Classification Model in One Hour (EN)
Vincent Houdebine, Data Scientist, Dataiku
10:45 - 12:15
Exclusive Workshop
Building and Deploying Your Image Classification Model in One Hour (EN)During this workshop, you will learn how you can use Dataiku DSS to build a Deep Learning model for Image classification without a single line of code or deep learning expertise. Step by step, you’ll explore different ways to leverage existing state-of-the art deep learning models in your own projects. Throughout the workshop, you will build your own image classifier using a pre-trained model and deploy it to a production environment to perform real-time predictions on images.
TBD
10:45 - 12:15
Exclusive Workshop
11:00
11:15
Using Deep Learning to rank and tag millions of hotel images (EN)
Tanuj Jain, Data Scientist, idealo internet GmbH | Christopher Lennan, Senior Data Scientist, idealo internet GmbH
11:15 - 11:45
Online Business
Using Deep Learning to rank and tag millions of hotel images (EN)At idealo.de (a leading price comparison website in Europe), we have a dedicated service to provide hotel price comparisons (hotel.idealo.de). For each hotel, we receive dozens of images and face the challenge of composing image galleries that are attractive and at the same time help our users to make informed decisions. Given that we have millions of hotel offers, we end up with more than 100 million images for which we need both an attractiveness assessment and a tag (e.g. a “bathroom” or “bedroom” tag)...
Fun with visual similarity search - Content-based image retrieval (CBIR) with Neural Networks (EN)A *brief introduction to CBIR with neural networks*: the general setup and architecture, feature representations, similarity measures, metrics and losses, datasets, different ways of training, common problems, and differences to classic computer vision algorithms. 2. *Lessons learned*: how RoomAR uses CBIR, hands-on implementation of CBIR with PyTorch, speeding up the search, and some (fun) ideas of what you can do with this setup.
11:30
11:45
I Never Meta-Data I Didn't Like (EN)
Colin Clark, Head of Global Data Engineering, WayFair
11:45 - 12:15
Online Business
I Never Meta-Data I Didn't Like (EN)An overview and demonstration of how to use meta-data for data driven ROI.
Know your jump - Uniting NLP and quantitative financial analytics to explain jumps in asset prices (EN)When in 1976, Robert Merton introduced jumps to the modelling of stock prices, he attributed the occurrence of such to
12:00
12:15
Lunch Break
12:15 - 13:45
Lunch Break
12:15 - 13:45
Lunch Break
12:15 - 13:45
12:30
12:45
13:00
13:15
13:30
13:45
Data Ethics (EN)
Alexander Borek, Global Head of Data & Analytics, Volkswagen Financial Services AG | Benno Blumoser, Innovation Head of Siemens AI Lab, Siemens | Prof. Dr. Ulrike Reisach, Commissioner for International Affairs Information Management Department, HNU | Jörg Bienert, Vorsitzender KI Bundesverband, Geschäftsführer aiso-lab
13:45 - 14:45
Panel
Productionizing Machine Learning Models - Lessons Learned in the Hadoop Ecosystem and the Way Ahead (EN)
Steffen Bunzel, Data Scientist, Alexander Thamm GmbH | Simon Weiß, Data Scientist, Alexander Thamm GmbH
13:45 - 15:15
Deep Dive
Productionizing Machine Learning Models - Lessons Learned in the Hadoop Ecosystem and the Way Ahead (EN)The deployment of machine learning models can be challenging. Especially in the context of distributed systems: Python being the dominant language among data scientists creates frictions when integrating with JVM-based tools such as Spark or managing application dependencies on clusters of heterogenous machines. Many data scientists developing on such systems struggle with the subtleties of these challenges. This presentation will share lessons learned working on large-scale Hadoop clusters and examine the most promising approaches to alleviate common issues. In particular, we will discuss our experience with leveraging containerization to tackle the dependency management challenge from a data scientist\\\'s point of view.
HPCC Systems - A Hidden Champion in Big Data Processing (EN)
Fabian Fier | PhD Student | Humboldt-Universität zu Berlin
13:45 - 15:15
Exclusive Workshop
HPCC Systems - A Hidden Champion in Big Data Processing (EN)HPCC Systems is an open-source big data system. It is developed by LexisNexis® Risk Solutions and used for credit ratings, fraud detection, anti money laundering, and many more enterprise applications. The system is based on the query language ECL that gets compiled down to C++ and machine code to be automatically deployed and executed on a compute cluster. In this workshop, we\'ll walk through the architecture of HPCC Systems, its capabilities and popular extensions (ML, visualization, connectors to other systems), and learn basics of its main query language ECL. Users of other big data systems such as Spark or Flink will feel familiar with the dataflow-oriented query language, the data types, and the available operators. However, the workshop is open to everyone interested in the topic without prior knowledge.
TBD
13:45 - 15:15
Exclusive Workshop
14:00
14:15
TBD
14:15 - 14:45
Data Visualization
14:30
14:45
data.networking(0)
Leading Topic: Data Ethics
14:45 - 15:15
Special
A Practical Guide to AI, Machine Learning, and Data Science (EN)
Ian Swanson, Vice President of Product AI/ML | Oracle
14:45 - 15:15
AI in your Enterprise
A Practical Guide to AI, Machine Learning, and Data Science (EN)Eager to adopt AI in your enterprise? Get an inside look at Oracle\'s platform AI solutions including new approaches using machine learning and data science. There is a seismic shift among Enterprises to harness more and more transformational technologies to improve their customer experiences, drive greater revenues, and lower operational costs. In this talk, we will cover Oracle’s strategy and solutions for AI across all of Oracle cloud platform including the pervasive mix of AI, Machine Learning across all of our services portfolio. See new advancements in data science and learn ways to develop and build new AI-based applications. We\'ll hear some of our customer success stories to date, and provide a personal pathway for enterprises to adopt these technologies based on where they are in their transformational journey.
15:00
15:15
Coffee Break
15:15 - 15:45
Coffee Break
15:15 - 15:45
Coffee Break
15:15 - 15:45
15:30
15:45
Peak Spotting — managing the capacity of Germany's long distance rail network with advanced visualisations (EN)
Mathias Richter, Senior Referent Digitale Transformation, DB Fernverkehr | Christian Laesser, Freelance Interaction Designer & Data Visualization Designer, Deutsche Bahn AG | Stephan Thiel, Co-Founder & Managing Director, Studio NAND
15:45 - 16:15
Transport & Industry
Peak Spotting — managing the capacity of Germany's long distance rail network with advanced visualisations (EN)A continuously increasing number of long-distance passengers requires a simple and fast identification of traffic corridors and trains with high load factors. In order to prevent over-utilisation of trains, tabular presentations of forecast and booking figures for individual trains were previously used...
Smart Training of ML Models in Audio- and Video Mining (EN)
Dr. Annina Neumann, VP Data Technology, ProSiebenSat.1 Media SE | Sebastian Schaal, Founder, Luminovo
15:45 - 16:15
Data in Media Companies
Smart Training of ML Models in Audio- and Video Mining (EN)The need for training data for machine learning algorithms is still incredibly high and is constantly growing with the growing use of artificial intelligence. Many companies are therefore faced with the challenge of reluctant to use methods such as deep learning because training the models would be too complex and time-consuming. At the same time, however, models available on the market are usually not directly applicable and do not fit optimally to one\\\\\\\'s own needs...
Demystifying the neural network black box: An interactive session on understanding decisions made by Convolutional Neural Networks (EN)
Tanuj Jain, Data Scientist, idealo internet GmbH Christopher Lennan, Senior Data Scientist, idealo internet GmbH
15:45 - 17:15
Deep Dive
Demystifying the neural network black box: An interactive session on understanding decisions made by Convolutional Neural Networks (EN)Convolutional Neural Networks (CNN) are state of the art when it comes to computer vision tasks, such as image recognition and object detection. However, due to the high amount of architectural complexity, it is often difficult to interpret the decisions made by these networks. Luckily, there are several techniques available which can enhance our comprehension of CNN decisions. These techniques are generally divided into attribution and visualisation methods...
Deep dive into Machine Learning with the Oracle Platform (incl. live demo) (EN)
Mats Stellwall, Data Scientist, Oracle EMEA
15:45 - 17:15
Exclusive Workshop
Deep dive into Machine Learning with the Oracle Platform (incl. live demo) (EN)In this workshop we will do a in-depth walkthrough on how you can use machine learning by a single click as part of your visualizations and analysis, how you can build Machine Learning models using Python/R code with notebooks against Big Data and Relational Data and even how you can do machine learning using good old SQL. Everything using Oracle’s state of the art Cloud Infrastructure.
TBD
15:45 - 17:15
Exclusive Workshop
16:00
16:15
Two years of Data Science in a Fujitsu factory (EN)
Alena Fojtík, Senior Data Scientist, Fujitsu TDS GmbH
16:15 - 16:45
Transport & Industry
Two years of Data Science in a Fujitsu factory (EN)When talking about data science projects we often focus on algorithms and results. But when you start a data science project from scratch in a factory there are a lot of different problems that need to be tackled: where to install a sensor in order to get data, how to involve external parties as the maker of the machines, defining what is acceptable data quality.... In this talk I want to discuss the challenges we faced and what we learned when we used data science in the Fujitsu factory in Augsburg in order to improve run time and quality.
Predictive Road Condition (EN)
Dr. Michael Unterreiner, Projektleiter, Porsche AG
16:15 - 16:45
Data & AI in Automotive
Predictive Road Condition (EN)The driving situations, the dynamic condition of the vehicle and the road condition are of high relevance in order to return the vehicle from critical situations, in particular with adverse weather-related road conditions, into a safe condition. The subject of this presentation is to determine road conditions and to derive a prediction of these with black data.
16:30
16:45
Anomaly detection in customs area (EN)
Michael Beckmann, Tax Manager & IT, Henkel AG & Co. KGaA
16:45 - 17:15
Transport & Industry
Anomaly detection in customs area (EN)The search for anomalous transactions was performed manually on historical data. A check for previously unknown anomalies and attribute constellations is hardly possible with manually defined rules. The aim of the project is to automatically detect anomalies and unwanted deviations using intelligent and learning procedures. The project therefore focused on advanced technologies (e.g. neural networks).
17:00
17:15
Beer Break
17:15 - 17:45
Beer Break
17:15 - 17:45
Beer Break
17:15 - 17:45
17:30
17:45
AI impact on P&L (EN)
Dr. Holger Kömm, Director Data Science Lab, Adidas AG | Alexander Borek, Global Head of Data & Analytics, Volkswagen Financial Services AG | Dat Tran, Head of Data Science, idealo.de | Vidya Munde-Müller, Founder & Ambassador, Women in AI | Marcus Hartmann, Chief Data Officer, ProSiebenSat1 Media SE | Dr. Sébastien Foucaud, Vice-President Data Science, XING
17:45 - 18:45
Panel
Data Science Kickstart in Germany (EN)
Students of ReDI School of Digital Integration | Klaus Roßmann
17:45 - 18:45
Special
18:00
18:15
18:30
18:45
The legendary Data Festival Party
with Drinks, Food & Live Music.
18:45 - 00:00
19:00
19:15
19:30
19:45
20:00
20:15
20:30
20:45
21:00
21:15
21:30
21:45
22:00
22:15
22:30
22:45
23:00
23:15
23:30
23:45

data.stage

festival.stage

tech.stage

work.shop(0)

work.shop(1)

  • TBD
    10:45 - 12:15
  • TBD
    13:45 - 15:15
  • TBD
    15:45 - 17:15
No events available!