Speaker: Eugene Kirpichov

Cloud Dataflow Staff SE @Google

Eugene Kirpichov is a Staff Software Engineer on the Cloud Dataflow team at Google, where he works on the Apache Beam programming model and APIs. Previously, he worked on Cloud Dataflow’s autoscaling and straggler elimination techniques. Eugene is interested in programming language theory, data visualization, and machine learning.

Find Eugene Kirpichov at

Talk : A Whirlwind Overview of Apache Beam

Tracks

  • Deep Learning Applications & Practices

    Deep learning lessons using tooling such as Tensorflow & PyTorch, across domains like large-scale cloud-native apps and fintech, and tacking concerns around interpretability of ML models.

  • Predictive Data Pipelines & Architectures

    Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Real-world Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.