The NVIDIA Institute (DLI) and XENON invite you to attend the Fundamentals of Deep Learning – Multiple Data Types hands-on workshop on:
Thursday April 11th
9:00am – 5:00pm
Monash University – Seminar 1,
Level 7, 30 Collins St Melbourne VIC 3000
Early bird: ONLY $395 inc GST
General Admission: $550 inc GST
About This Workshop
This workshop explores how convolution and recurrent neural networks can be combined to generate effective descriptions of content within images and video clips.
Learn how to train a network using TensorFlow and the Microsoft Common Objects in Context (COCO) dataset to generate captions from images and video by:
- Implementing Deep Learning workflows like image segmentation and text generation
- Comparing and contrasting data types, workflows, and frameworks
- Combining computer vision and natural language processing
Upon completion, you’ll be able to solve problems that require multiple types of data inputs. You will receive a Fundamentals certificate from Institute!
Attendees MUST bring their own laptops.
09:30 Image Segmentation with TensorFlow (hands-on lab)
11:00 Tea Break
11:15 Word Generation with TensorFlow (hands-on lab)
13:30 Word Generation with TensorFlow (hands-on lab) [continued]
14:45 Image and Video Captioning by Combining CNNs and RNNs (hands-on lab)
15:45 Tea Break
16:00 Image and Video Captioning by Combining CNNs and RNNs (hands-on lab) [continued]
17:00 Closing Comments and Questions
Lunch and Coffee provided by XENON
Familiarity with basic Python (functions and variables) and prior experience training neural networks is expected.
Instructor: Titus Tang
Titus Tang is a Deep Learning consultant at Alpha One AI and a lecturer and tutor at Monash University, sharing his knowledge in the areas of AI, computer systems and software engineering. He is also the founder of Monash Deep Learning Workshops.
Detailed Course Outline
||Introduction to , situations in which it is useful, key terminology, industry trends, and challenges.|
|Image Segmentation with TensorFlow||
||Hands-on exercise: Segment MRI images to measure parts of the heart using tools such as TensorBoard and the TensorFlow Python API.|
|Word Generation with TensorFlow||
||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.|
|Image and Video Captioning||
||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.|
||Review of concepts and practical takeaways.|
Workshop Setup Instructions:
- Create an NVIDIA Developer account at http://courses.nvidia.com/join.
- Make sure that WebSockets works for you:
- Test your laptop at http://websocketstest.com
- Under ENVIRONMENT, confirm that “WebSockets” is checked yes.
- Under WEBSOCKETS (PORT 80), confirm that “Data Receive,” “Send,” and “Echo Test” are checked yes.
- If there are issues with WebSockets, try updating your browser. We recommend Chrome, Firefox, or Safari for an optimal performance.
- Once onsite, visit http://courses.nvidia.com/dli-event and enter the event code provided by the instructor.
This workshop is brought to you by: