Deep Learning and the Challenges of Scale
Many of the deep learning problems which industries are trying to tackle are complex. While it is relatively easy to build an early proof of concept (POC) of a system, it takes a huge amount of effort to build a solution that meets all functional and non-functional requirements.
For example, it’s straightforward to build a POC for self-driving vehicles that will drive across a small number of streets with human supervision. On the other hand, building a self-driving car which is robust and safe is an engineering feat requiring petabytes of data for training and validation.
In this webinar we tackleed the key challenges faced when developing complex deep learning systems and focus on the scalability of the training process.
By watching this webinar replay, you’ll learn:
- The key algorithmic challenges involved in large scale training
- The choice of the algorithm used for distributed training and the degradation of performance associated with large batch sizes
- Engineering challenges involved in designing and utilising large-scale training
WEBINAR REPLAY REGISTRATION
Presented By
Adam Henryk Grzywaczewski
Deep Learning Solution Architect, NVIDIA
Adam Grzywaczewski is a deep learning solution architect at NVIDIA, where his primary responsibility is to support a wide range of customers in the delivery of their deep learning solutions. Adam is an applied research scientist specializing in machine learning with a background in deep learning and system architecture. Previously, he was responsible for building up the UK government’s machine-learning capabilities while at Capgemini and worked in the Jaguar Land Rover Research Centre, where he was responsible for a variety of internal and external projects and contributed to the self-learning car portfolio.
 "Add Presenter 2's Title (ex: CMO, ABC Company)")
Add Presenter 2's Name (John Smith)
Add Presenter 2's Title (ex: CMO, ABC Company)
Add Presenter 2's Bio (2-3 Sentences)
 "Add Presenter 3's Title (ex: CMO, ABC Company)")
Add Presenter 3's Name (John Smith)
Add Presenter 3's Title (ex: CMO, ABC Company)
Add Presenter 3's Bio (2-3 Sentences)
 "Add Presenter 4's Title (ex: CMO, ABC Company)")
Add Presenter 4's Name (John Smith)
Add Presenter 4's Title (ex: CMO, ABC Company)
Add Presenter 4's Bio (2-3 Sentences)
HOSTED BY
