Together with BOSCH we invite you to a full day of learning more about the intersection of mobility and code. Get to know more about how modern mobility is defined by an intricate interplay of hardware and software and how cars are not only connected to the road, but also to the cloud.
Coding the Future of Mobility features a variety of talks and a workshop, that give you valuable insights into the world of mobility - wether you join in-person or online.
Together with Bosch we invite you to a full day of learning more about the intersection of mobility and code. Get to know more about how modern mobility is defined by an intricate interplay of hardware and software and how cars are not only connected to the road, but also to the cloud.
Coding the Future of Mobility features a variety of talks and a workshop, that give you valuable insights into the world of mobility - wether you join in-person or online.
In this talk we will introduce how to use the popular cloud service Databricks for
hosting Apache Spark applications for distributed data processing in combination with
Apache Airflow, an orchestration framework for ETL batch workflows. After a brief
exploration of the Databricks Workspace and the fundamentals of Airflow we will take a
deeper look into the functionality Databricks provides in Airflow for orchestrating its
workspace. Afterwards, we will find out how to extend and customize that functionality to
manage virtually every aspect of the Databricks Workspace from Airflow.
The talk does not require any prior knowledge of Databricks, Spark or Airflow but it does
assume familiarity with the fundamentals of the Python programming language especially
object oriented programming and REST api requests. The actual distributed data processing
with Apache Spark itself is not the focus of this talk.
Alan finished his Master degree from Karlsruhe Institute of Technology in Information Engineering and Management in 2020 before starting his career as a Machine Learning Engineer at inovex GmbH in Cologne, Germany. He (co-) authored two scientific papers in the area of machine learning published at major journals and conferences and is a regular contributor to the open source community.
DeepFace is the most popular facial recognition library nowadays. Users can build and run facial recognition with a few lines of code. In this talk, we are going to unbox DeepFace to understand how deep face recognition working.
I received my MSc in Computer Science from Galatasaray University in 2011.
I am a software engineer at Yapi Kredi Technology.
In March 2020 the world is completely blocked and people are lining up to shop or to the pharmacy or to buy basic necessities.
There have been many initiatives and among these I have created a worldwide map that allows anyone to check the estimated waiting times of supermarkets, pharmacies and places of interest.
In addition to this, I gave people the opportunity to check waiting times and correct them through a crowdsourcing mechanism.
All this, to be fast in development and in responding to requests, has exploited Redis with its geospatial indexes.
The opensource project has obtained more than 2Mln visits in about 3 months of life, until June 2020 when the pandemic slowed down.
In this talk we will see the architecture and the problems I encountered and solved with Redis.
I'm a passion & creative-driven developer who has a ton of other passions: basketball, cycling, and photography are a few of them.
Since 2014 I have lent my expertise in the software development and solution architect fields in Florence, Italy.
I've been working as a software engineer & solution architect for 7+ years in both product and consultancy companies, taking the best from both worlds.
I'm currently working as a Full Stack Engineer at Growens, where I'm developing and optimizing the email marketing platform in an Agile team (SCRUM).