Workshops at Data Day Seattle

As part of Data Day Seattle 2017, we have asked several of the speakers to come a day early and offer workshops. These are standalone workshops separate from Data Day Seattle. You do not have to have a ticket to Data Day, in order to sign up for these workshops. We are well familiar with the instructors for these workshops and endorse them without reservation.

Neo4j Fundamentals Training

(use the code Neo50 for 50% off this course)
This beginning level course will give you a foundational knowledge of graph databases and use cases. You'll learn all the getting-started basics, including data import and creation, basic modeling, and querying. Learn to use Neo4j's powerful query language, Cypher, and how it can drastically improve your connected data problems.
The course is best suited for anyone with an interest in database technology: developers, administrators, devops engineers, DBAs, business analysts and students.
You won’t need any previous experience with Neo4j, NOSQL databases or specific development languages.
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Hands-on Introduction to TinkerPop and the Gremlin Query Language

We originally commissioned this TinkerPop/Gremlin workshop for recent Graph Day conference held in Austin, January 2017. The workshop sold out and received rave reviews. When Josh offered it again at Graph Day in San Francisco, it sold out as well. We have asked Josh Perryman, of Expero, to come to Seattle and offer the course again in concunction with Data Day Seattle. As far as we know, this is currently the only TinkerPop / Gremlin training workshop in the world.
There will only be one section of this class, and enrollment is limited to 30. Don't miss this opportunity!
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Hands-on Introduction to NLP with TensorFlow

This class will teach you how to do natural language processing with deep learning in TensorFlow. We will start at the beginning with getting TensorFlow running on simple computations. We will explore the structure of the TensorFlow GitHub code so that you can understand it right from the source. From this beginning, we will explore applications such as learning word vectors, language models with recurrent neural networks, and text classification with convolutional neural networks. We will also cover a codebase that allows you to create powerful sequence-to-sequence models for machine translation and other tasks. And we will introduce the tensor2tensor codebase, which is a powerful generalization on the sequence-to-sequence framework. In addition to covering TensorFlow, we will teach you how to use TensorBoard to visualize both your computations and results.
Full details and registration info