Deep Dive into TensorFlow #5

WAITLIST ONLY

Please register HERE (http://bit.ly/2kAfBsG)as the venue needs full names for security purposes

Many thanks to RobotX Space, CloudMinds and ZGC Incubatorfor hosting and sponsoring the TensorFlow meetup!

Agenda:

6:30 - Doors open. Networking. Members meet each other. Pizza and beer

7:00 - Software Patterns in TensorFlow by Garrett Smith

7:45 - Q&A break

7:50 - Google's Neural Machine Translation System by Xiaobing Liu

8:30 - Q&A break

8:40 - Wrap-up.

DETAILED AGENDA:

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Software Patterns in TensorFlow

TensorFlow is a flexible, general purpose computational library that's used to implement a wide range of machine learning models. Its flexibility however presents a challenge: how do teams discover and apply effective software patterns in their projects? In this presentation, Garrett Smith, founder of Guild AI, will share his experience working with dozens of TensorFlow projects and discuss patterns that work well and those that don't when writing TensorFlow code.

Garrett will cover:

• Project structure
• Variable naming conventions
• Canonical functions and workflow
• Parameterization using flags
• Logging and retraining experiment results
• Conventions for serving trained models
• Lessons from TFLearn and Keras

Presenter: Garrett Smith, founder of Guild AI

Garrett Smith is founder of Guild AI, an open source toolkit that helps developers gain insight into their TensorFlow experiments. Garrett has over twenty years of software development experience and has managed teams across a wide range of product development efforts. His has expertise in building reliable, districuted back-end systems and in operations. Prior to founding Guild AI, Garrett led CloudBees PaaS division, which hosted hundreds of thousands of Java applications at scale. Garrett is a frequent instructor and speaker at software conferences and an active member of the Erlang community, maintaining several prominent open source projects.

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Google's Neural Machine Translation System

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based translation systems. In this talk, Xiaobing Liu will talk about the model architecture, word-pieces design, training algorithm and how to make training/serving faster. Xiaobing will mention about the zero-shot for Multilingual model as well.

Presenter: Xiaobing Liu, Google Brain Senior Software Engineer and Machine Learning Researcher

Xiaobing Liu is a Google Brain senior software engineer and machine learning researcher. In his work, Xiaobing focuses on Tensorflow and some key applications where Tensorflow could be applied to improve Google products, such as Google Search, Play recommendation and Google translation and so on.

WAITLIST ONLY

Please register HERE (http://bit.ly/2kAfBsG)as the venue needs full names for security purposes