Presentation: NVIDIA Jetson

Track: AI Meets the Physical World

Location: Cyril Magnin II

Duration: 12:50pm - 1:00pm

Day of week: Tuesday

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Abstract

  • Quick Overview of the TX2 hardware and TX2 Dev Kit
  • Software that runs on the TX2 Devkit

Examples: Supervised DL for Classification, Segmentation from the camera and RL projects

Note: This is a short talk. Short talks are 10-minute talks designed to offer breadth across the areas of machine learning, artificial intelligence, and data engineering. The short talks are focused on the tools and practices of data science with an eye towards the software engineer.

Speaker: Dana Sheahen

Robotics @Udacity

Dana currently works as a Curriculum Lead for Udacity leading their Robotics Nanodegree program content development in Mountain View, California. As a BSEE with an emphasis in software, she previously worked in a number of industry areas including automotive systems, medical instrumentation, and environmental data analysis. More recently, Dana obtained her Master’s in Computer Science from Georgia Tech with a specialty in Interactive Intelligence, and has focused on AI projects and AI education ever since.

Find Dana Sheahen at

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.