Presentation: TensorBoard: Visualizing Learning

Track: Hands-on Codelabs & Speakers Office Hours

Location: Mission

Duration: 12:45pm - 12:55pm

Day of week: Wednesday

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Abstract

Machine learning models, especially deep learning ones, can be complex. We walk through how to debug, monitor, and examine the decisions of a TensorFlow-based model using the TensorBoard suite of visualizations. 
This is an introduction to the TensorBoard Codelab.

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: Chi Zeng

Software Engineer @Google

Chi works on the TensorBoard suite of visualizations within Google Brain. He also works on the People+AI Research Initiative, which strives to make partnerships between people and artificial intelligence productive, enjoyable, and fair.

Find Chi Zeng at

Proposed Tracks

  • Real-World Data Engineering

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

  • Deep Learning Applications & Practices

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, computer vision.

  • AI Meets the Physical World

    The track where AI touches the physical world, think drones, ROS, NVidea, TPU and more.

  • Data Architectures You've Always Wondered About

    How did they do that? Real-time predictive pipelines at places like Uber, Self-Driving Cars at Google, Robotic Warehouses from Ocado in the UK, are all possible examples.

  • Applied ML for Software

    Practical machine learning inside the data centers and on software engineering teams.

  • Time Series Patterns & Practices

    Stocks, ad tech/real-time bidding, and anomaly detection. Patterns and practices for more effective Time Series work.