This workshop teaches you to apply deep learning techniques to a range of problems involving multiple data types through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows by performing neural network training on a fully-configured GPU accelerated workstation in the cloud. After a quick introduction to deep learning, you will advance to building deep learning applications for image segmentation, sentence generation, and image and video captioning, while simultaneously learning relevant computer vision, neural network, and natural language processing concepts. At the end of the workshop, you will be able to assess a broad spectrum of problems where you can apply deep learning.
- Duration: 8 hours
- Assessment Type: Multiple Choice
- Certification: Upon successful completion of this workshop, you will receive NVIDIA DLI Certification to prove subject matter competency and support professional career growth
- Prerequisites: Successful completion of ‘Fundamentals of Deep Learning for Computer Vision’ DLI course or equivalent. Familiarity with basic python (functions and variables) and prior experience training neural networks is expected
- Languages: English
- Tools, libraries, and frameworks: TensorFlow, TensorBoard
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Throughout 2019 XENON will be offering both Private and Public Workshops.
Interested? Contact us for latest course schedule.
LEARNING OBJECTIVES
At the conclusion of the workshop, you will have an understanding of the fundamentals of deep learning and be able to:
- Implement common deep learning workflows such as image segmentation and text generation
- Compare and contrast data types, workflows, and frameworks
- Combine deep learning powered computer vision and natural language processing to start solving sophisticated real-world problems that require multiple input data types
WHY DEEP LEARNING INSTITUTE HANDS-ON TRAINING?
- Learn how to build deep learning and accelerated computing applications across a wide range of industry segments such as Autonomous Vehicles, Digital Content Creation, Finance, Game Development, and Healthcare
- Obtain guided hands-on experience using the most widely used, industry-standard software, tools, and frameworks
- Attain real world expertise through content designed in collaboration with industry leaders such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC
- Earn NVIDIA DLI Certification to prove your subject matter competency and support professional career growth
- Access courses anywhere, anytime with a fully configured GPU-accelerated workstation in the cloud
Interested? Contact us to book into the next course.
CONTENT OUTLINE
| Components | Description | |
|---|---|---|
| Introduction (45 mins) |
|
Introduction to deep learning, situations in which it is useful, key terminology, industry trends, and challenges. |
| Break (15 mins) | ||
| Image Segmentation with TensorFlow (120 mins) |
|
Hands-on exercise: Segment MRI images to measure parts of the heart using tools such as TensorBoard and the TensorFlow Python API. |
| Break (60 mins) | ||
| Word Generation with TensorFlow (120 mins) |
|
Hands-on exercise: a Recurrent Neural Network to understand both images and text, and to predict the next word of a sentence using the MSCOCO (Microsoft Common Objects in Context) dataset. |
| Break (15 mins) | ||
| Image and Video Captioning (120 mins) |
|
Hands-on exercise: Train a model that generates a description of an image from raw pixel data by combining outputs of multiple networks (CNNs and RNNs) through concatenation and/or averaging. |
| Summary (15 mins) |
|
Review of concepts and practical takeaways. |
