Put open source to work
July 16–17, 2018: Training & Tutorials
July 18–19, 2018: Conference
July 18–19, 2018: Conference
Portland, OR
TensorFlow Day
9:00am–5:00pm Tuesday, July 17, 2018
Sponsored
Location: B115-116
Location: B115-116
TensorFlow Day is open to all pass holders
Sponsored by:
The machine learning revolution is powered by open source! The developers of TensorFlow believe machine learning should be available to all, so we’re holding a day at OSCON to talk about the project, and explore collaboration.
We’ll have a full day of talks from TensorFlow contributors, great demos, and an open hacking room where you can get hands-on with TensorFlow, and learn how you can be a part of the project.
Attendance is open to any registered OSCON attendee, including expo hall passes. Register here.
Hacking Room
Alongside the session room, we’ll have a room set for groups to collaboratively work on TensorFlow-related projects. Drop in for as long as you want to collaborate and meet like-minded TensorFlow developers. At the end of the day, each group will get the chance to report back to the main presentation room. Read more ...
Tuesday, 07/17/2018
8:00am
8:00am–9:00am Tuesday, 07/17/2018
Location: Portland Ballroom Foyer & Pre-function C
Morning coffee service
(1h)
9:00am
9:00am–9:05am Tuesday, 07/17/2018
Edd Wilder-James (Google)
Edd Wilder-James (Google)
Average rating:
(5.00, 1 rating)
Edd Wilder-James opens TensorFlow Day.
Read more.
9:05am
9:05am–9:40am Tuesday, 07/17/2018
Sandeep Gupta (Google)
Sandeep Gupta (Google)
Average rating:
(4.00, 1 rating)
TensorFlow is one of the world's biggest open source projects, and it continues to grow in adoption and functionality. Sandeep Gupta shares major recent developments and highlights some future directions for the project.
Read more.
9:40am
9:40am–10:15am Tuesday, 07/17/2018
Hallie Benjamin (Google)
Location: B115-116
Hallie Benjamin (Google)
Average rating:
(5.00, 1 rating)
Hallie Benjamin offers an introduction to the emerging field of machine learning fairness, explains how it's relevant to the developer community, and shares resources for learning more.
Read more.
10:15am
10:15am–10:30am Tuesday, 07/17/2018
Edd Wilder-James (Google)
Edd Wilder-James (Google)
The hacking room runs parallel to the sessions. Stop by to listen to table leaders describe the topics for their tables and decide which you want to visit.
Read more.
10:30am
10:30am–11:00am Tuesday, 07/17/2018
Location: Portland Ballroom Foyer & Pre-function C
Morning Break
(30m)
11:00am
11:00am–11:30am Tuesday, 07/17/2018
Gunhan Gulsoy (Google Brain)
Gunhan Gulsoy (Google Brain)
Average rating:
(4.00, 1 rating)
Gunhan Gulsoy shares the inside story of how the very popular source project TensorFlow is kept running and sheds light on how TensorFlow is continuously built and tested and how everything is kept green through dozens of changes daily.
Read more.
11:30am
11:30am–12:00pm Tuesday, 07/17/2018
Average rating:
(3.00, 1 rating)
We typically interact with a web app by clicking and typing information. However, there are situations when this interaction is not convenient or possible. Voice is a much more common and convenient method for interaction. Ton Ngo and Yi-Hong Wang explain how TensorFlow.js can help a web-based electronic health record system leverage deep learning models to make this voice interface possible.
Read more.
12:00pm
12:00pm–12:30pm Tuesday, 07/17/2018
Sherol Chen (Google)
Location: B115-116
Sherol Chen (Google)
Average rating:
(5.00, 2 ratings)
Sherol Chen offers an overview of Project Magenta, a research project exploring the role of machine learning in the process of creating art and music. Primarily this involves developing new deep learning and reinforcement learning algorithms for generating songs, images, drawings, and other materials.
Read more.
12:30pm
12:30pm–1:30pm Tuesday, 07/17/2018
Location: Convention Center Plaza
Food Truck Lunch sponsored by CA Technologies
(1h)
1:30pm
1:30pm–2:00pm Tuesday, 07/17/2018
Hannes Hapke (SAP ConcurLabs)
Hannes Hapke (SAP ConcurLabs)
Average rating:
(5.00, 3 ratings)
Developing deep learning models with TensorFlow is often only half of the story. To be useful to the public, the model needs to be deployed. Hannes Hapke explains how to deploy your TensorFlow model easily with TensorFlow Serving, introduces an emerging project called Kubeflow, and highlights some deployment pitfalls like model versioning and deployment flow.
Read more.
2:00pm
2:00pm–2:30pm Tuesday, 07/17/2018
Paige Bailey (Microsoft)
Paige Bailey (Microsoft)
Average rating:
(5.00, 1 rating)
Machine learning offers a powerful toolkit for building complex predictive systems. These models can provide immense business value and are often deployed in high-consequence environments, but it can be extremely dangerous to think of those quick wins as coming for free. Paige Bailey explains what happens when your data changes over time and fresh models must be produced continuously.
Read more.
2:30pm
2:30pm–3:00pm Tuesday, 07/17/2018
Fabio Buso (Logical Clocks AB)
Fabio Buso (Logical Clocks AB)
Fabio Buso offers demonstrations of frameworks for building distributed TensorFlow applications on the Hops platform and walks you through the whole model lifecycle, from debugging and visualizing models on TensorBoard to parallel experimentation and distributed training (with the help of Spark) to model deployment and inferencing using TensorFlow Serving and Kubernetes.
Read more.
3:00pm
3:00pm–3:30pm Tuesday, 07/17/2018
Location: Portland Ballroom Foyer & Pre-function C
Afternoon Break sponsored by Aspen Mesh
(30m)
3:30pm
3:30pm–4:00pm Tuesday, 07/17/2018
Scott Soutter (IBM),
Jason Furmanek (IBM)
Scott Soutter (IBM),
Jason Furmanek (IBM)
Average rating:
(4.00, 1 rating)
Data scientists and model developers routinely trade off data size or model complexity in order to fit within limited GPU memory resources. Scott Soutter and Jason Furmanek discuss IBM's updates to TensorFlow, which dramatically increase memory and model size. This technique, which is being upstreamed to the open source community, provides the ability to load the entire model in system memory.
Read more.
4:00pm
4:00pm–4:30pm Tuesday, 07/17/2018
Average rating:
(4.50, 2 ratings)
R has a rich history as an open source statistical computing project and is a mainstay of data science. Gabriela de Queiroz and Augustina Ragwitz explain how R has gotten together with TensorFlow to provide a great toolkit for deep learning.
Read more.
4:30pm
4:30pm–4:50pm Tuesday, 07/17/2018
Average rating:
(4.50, 2 ratings)
Alex Kari and Al Kari walk you through the code to download a Pokémon images dataset, train and freeze a TensorFlow model on Google Colaboratory, and compile and deploy it on the Google AIY Vision kit (which runs TensorFlow on a Raspberry Pi) to identify and provide stats on any Pokémon with its camera.
Read more.
4:50pm
4:50pm–5:00pm Tuesday, 07/17/2018
Edd Wilder-James (Google)
Edd Wilder-James (Google)
Listen in as hacking room participants share what they've achieved during the day. Then Edd Wilder-James closes TensorFlow Day.
Read more.
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