Speaker: Veda Shankar

Senior Developer Advocate @MapD

Veda Shankar is a Developer Advocate at MapD working actively to assist the user community to take advantage of MapD’s open source analytics platform. He is a customer oriented IT specialist with a unique combination of experience in product development, marketing and sales engineering. Prior to MapD, Veda worked on various open source software defined data center products at Red Hat.

Find Veda Shankar at

Talk : Very Large Datasets With the GPU Data Frame

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.