14–17 Oct 2019

2-Day Training Courses

All training courses take place 9:00 – 17:00, Monday, 14 October – Tuesday, 15 October. In order to maintain a high level of hands–on learning and instructor interaction, each training course is limited in size.

Participants should plan to attend both days of this 2-day training course. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Tuesday.

Monday, 14 October - Tuesday, 15 October

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9:00 - 17:00 Monday, 14 October & Tuesday, 15 October
Location: Hilton Meeting Room 3/4
Michael Cullan (The Data Incubator)
The TensorFlow library provides computational graphs with automatic parallelization across resources, ideal architecture for implementing neural networks. Michael Cullan walks you through TensorFlow's capabilities in Python from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications. Read more.
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9:00 - 17:00 Monday, 14 October & Tuesday, 15 October
Location: Westminster Suite
Rich Ott (The Data Incubator)
PyTorch is a machine learning library for Python that allows you to build deep neural networks with great flexibility. Its easy-to-use API and seamless use of GPUs make it a sought-after tool for deep learning. Join Ana Hocevar to get the knowledge you need to build deep learning models using real-world datasets and PyTorch. Read more.
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9:00 - 17:00 Monday, 14 October & Tuesday, 15 October
Location: Hilton Meeting Room 1/2
Angie Ma (Faculty), Richard Sargeant (Faculty)
Angie Ma and Richard Sargeant offer a condensed introduction to key AI and machine learning concepts and techniques, showing you what is (and isn't) possible with these exciting new tools and how they can benefit your organization. Read more.
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9:00 - 17:00 Monday, 14 October & Tuesday, 15 October
Location: Park Suite
Umberto Michelucci (TOELT LLC)
Convolutional neural networks (CNNs) are at the basis of many algorithms that deal with images from image recognition and classification to object detection. Umberto Michelucci uses practical examples to walk you through how to develop convolutional neural networks, how to use pretrained networks, and even how to teach a network to paint. TensorFlow or Keras will be used for all examples. Read more.

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