You will learn how to train a network using TensorFlow and the MSCOCO dataset to generate captions from images and video by:
Upon completion, you will be able to solve deep learning problems that require multiple types of data inputs.
The course focuses on being able to use the techniques and offers hands-on training under expert guidance. You can ask about everything from how to start to how to move on if you are stuck. And the best part is that the next day you will be able to continue using deep learning back at work.
A laptop with Google Chrome, Firefox or Safari (no special hardware like GPUs required).
Create an account on the DLI Platform (instructions will be e-mailed a few days before the course).
The course provides an insight into what artificial intelligence and deep learning are. Both in terms of how complicated and how uncomplicated the area is. Now I can have a better dialogue with both colleagues and the companies we collaborate with in this area. It’s a good way to get a feel of it. As for an introduction, it has been really good and tool-based.
Mikael Knudsen, Development Manager, Aarhus University School of Engineering, Electrical and Computer Engineering
|9:00||Deep Learning Demystified and Applied Deep Learning (lecture)|
|10:00||Image Segmentation with TensorFlow (lab*)|
|12:00||Lunch break (lunch not included)|
|13:00||Word Generation with TensorFlow (lab*)|
|15:15||Image and Video captioning by Combining CNNs and RNNs (lab*)|
|17:15||Q&A and closing comments|
This workshop is meant for developers, data scientists and researchers with a basic understanding of deep learning concepts.
Prerequisites: Basic programming skills (C/C++, Python or similar)
Duration: 8 hours
*Please note that attendees MUST bring their own laptops.
If you have any questions, please send an e-mail to email@example.com.
We also offer a course in Computer Vision.
This workshop is brought to you by:
Organised by NVIDIA Deep Learning Institute and the Alexandra Institute
Henrik Pedersen and Mads Thoudahl are our deep learning experts. They know all about the technologies and have helped many businesses use deep learning.
Henrik Pedersen is a Senior Computer Vision Engineer, PhD, at the Alexandra Institute and we have chosen him as educator. Over his career, Henrik has been in various academic positions, covering research and teaching in computer vision and deep learning. His interests lie in exploring deep learning techniques for object detection and recognition using photorealistic, synthetic images for training. Henrik is an experienced educator and has played a key role in building up the vibrant deep learning community at the Alexandra Institute.
Mads Thoudahl specialises in machine learning and has a Master’s degree in computer science from the University of Copenhagen. He has a broad-based profile that spans the field between data analysis, modelling, simulation and visualisation, including cluster architecture and parallel programming in simulation of physical systems.