NVIDIA DLI WORKSHOPS
NVIDIA Deep Learning Institute (DLI) offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing.
DLI and University of Sannio (Dept. of Engineering) with University of Salerno (Dept. of Innovation Systems) are excited to announce the 2019 series of practical Deep Learning workshops exclusively for verifiable academic students, staff, and researchers.
Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities.
In this workshop, you’ll learn the basics of deep learning by training and deploying neural networks. You’ll learn how to:
- Implement common deep learning workflows, such as image classification and object detection
- Experiment with data, training parameters, network structure, and other strategies to increase performance and capability
- Deploy your neural networks to start solving real-world problems
Upon completion, you’ll be able to start solving problems on your own with deep learning.
- Jul 11, 09h00 - University of Salerno, Dept. of Innovation Systems
- Feb 4, 09h00 - University of Ferrara, Dept. of Physics and Earth Sciences
Learn the latest deep learning techniques to understand textual input using natural language processing (NLP). You’ll learn how to:
- Convert text to machine-understandable representations and classical approaches
- Implement distributed representations (embeddings) and understand their properties
- Train machine translators from one language to another
Upon completion, you’ll be proficient in NLP using embeddings in similar applications.
- Jul 22, 09h00 - University of Salerno, Dept. of Innovation Systems
This workshop explores how convolutional 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 deep learning problems that require multiple types of data inputs.
- Sep 16, 09h00 - University of Salerno, Dept. of Innovation Systems
- Feb 05, 09h00 - University of Ferrara, Dept. of of Physics and Earth Sciences